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| computer vision inventory management: Computer Vision, Pattern Recognition, Image Processing, and Graphics R. Venkatesh Babu, Mahadeva Prasanna, Vinay P. Namboodiri, 2020-11-16 This book constitutes the refereed proceedings of the 7th National Conference on Computer Vision, Pattern Recognition, Image Processing, and Graphics, NCVPRIPG 2019, held in Hubballi, India, in December 2019. The 55 revised full papers 3 short papers presented in this volume were carefully reviewed and selected from 210 submissions. The papers are organized in topical sections on vision and geometry, learning and vision, image processing and document analysis, detection and recognition. |
| computer vision inventory management: Computer Vision and Image Recognition Venkata Sathya Kumar koppisetti, 2024-07-25 Computer Vision and Image Recognition transformative technology enabling machines to interpret and understand visual information. This book explores the foundational theories and techniques in computer vision, covering critical topics such as image processing, feature extraction, object detection, and classification. With applications spanning from autonomous vehicles to medical imaging, it provides a comprehensive overview of algorithms and deep learning methods that power visual perception in machines. Aimed at students, researchers, and practitioners, this guide bridges theoretical concepts with real-world applications, emphasizing advancements in AI-driven image recognition and the future of intelligent visual systems. |
| computer vision inventory management: Computer Vision Fouad Sabry, 2024-04-27 What is Computer Vision Computer vision tasks include methods for acquiring, processing, analyzing, and comprehending digital images, as well as the extraction of high-dimensional data from the actual world in order to provide numerical or symbolic information, such as, for example, in the form of judgments. In the context of this discussion, understanding refers to the process of transforming visual pictures into descriptions of the environment that are comprehensible to thinking processes and have the ability to evoke appropriate action. It is possible to interpret this picture understanding as the process of extracting symbolic information from image data by making use of models that have been created with the assistance of learning theory, geometry, physics, and computer science. How you will benefit (I) Insights, and validations about the following topics: Chapter 1: Computer vision Chapter 2: Machine vision Chapter 3: Image analysis Chapter 4: Image segmentation Chapter 5: Optical flow Chapter 6: Motion detection Chapter 7: Gesture recognition Chapter 8: Pose (computer vision) Chapter 9: Rita Cucchiara Chapter 10: Stereo cameras (II) Answering the public top questions about computer vision. (III) Real world examples for the usage of computer vision in many fields. Who this book is for Professionals, undergraduate and graduate students, enthusiasts, hobbyists, and those who want to go beyond basic knowledge or information for any kind of Computer Vision. |
| computer vision inventory management: COMPUTER VISION: IMAGE RECOGNITION AND ANALYSIS TECHNIQUES Prof. Munindra Lunagaria, Mr. Yogesh Kumar Podapati, Dr. Sheshang D. Degadwala, Saikumar Tara, 2023-07-04 Computer vision is what we call the practice of using computer-based imaging where there is no human interaction in the visual loop at any point in the process. The photos are analyzed by a computer, which then takes appropriate action depending on their results. Computer vision systems are used in a variety of medical disciplines, and the only thing that can be said with absolute confidence is that the scope of these systems' applications will continue to expand in the future is the only thing that can be declared with absolute certainty. processing one or more digital photographs in order to generate valuable inferences about real-world physical objects and situations by computing the features of the 3D environment. This processing may be done with either one picture or all of them together. generating an accurate and comprehensive description of a real world object based on a photograph of that thing. The discipline of computer vision came into being as a consequence of efforts to model image processing utilizing the several approaches that are accessible within the discipline of machine learning. The field of computer vision makes use of machine learning to search for patterns in images with the end goal of deciphering such patterns. The field of computer vision entails the practice of teaching computers to recognize objects based on the digital still photos or moving movies that are sent into them. Finding methods through which jobs can be automated that now rely on the human visual system is the objective here. Image processing is one of the various methods that are utilized in the execution of this approach. The subfield of artificial intelligence (AI) known as computer vision is an absolutely necessary component in order for computers and other types of systems to be able to respond or provide suggestions based on visual data such as digital photos, movies, and other types of inputs. The same way that artificial intelligence makes it possible for computers to think, computer vision makes it possible for computers to see, comprehend, and observe. Computer vision and human vision are functionally comparable; the primary difference is that human eyesight developed far earlier than computer vision. The capacity of human beings to learn to differentiate between different things, their distances from one another, whether or not the items are moving |
| computer vision inventory management: Investigations in Pattern Recognition and Computer Vision for Industry 4.0 Chowdhary, Chiranji Lal, Swain, Basanta Kumar, Kumar, Vijay, 2023-09-07 The approaches to computer vision have undergone a long journey in recent years, but still, innovations are continuing with leverage increases in computing power, new data availability, and new ways to leverage machine-learning algorithms. As a branch of artificial intelligence (AI), computer vision brings meaningful information from images and videos. Such innovations help communicators to run better campaigns, amplify messages further, and stand out in a noisy, crowded marketplace. Investigations in Pattern Recognition and Computer Vision for Industry 4.0 provides a holistic discussion of the new practical applications and use cases of computer vision and communications. Covering topics such as social media filters, mobile computer vision, and AI-powered image editing, this book is ideal for academicians, researchers, postgraduate students, professional data analysts, research and development centers, organizations dealing with healthcare informatics, and IT firms. |
| computer vision inventory management: Computer Vision Mrinal Kanti Bhowmik, 2024-03-07 This comprehensive textbook presents a broad review of both traditional (i.e., conventional) and deep learning aspects of object detection in various adversarial real-world conditions in a clear, insightful, and highly comprehensive style. Beginning with the relation of computer vision and object detection, the text covers the various representation of objects, applications of object detection, and real-world challenges faced by the research community for object detection task. The book addresses various real-world degradations and artifacts for the object detection task and also highlights the impacts of artifacts in the object detection problems. The book covers various imaging modalities and benchmark datasets mostly adopted by the research community for solving various aspects of object detection tasks. The book also collects together solutions and perspectives proposed by the preeminent researchers in the field, addressing not only the background of visibility enhancement but also techniques proposed in the literature for visibility enhancement of scenes and detection of objects in various representative real-world challenges. Computer Vision: Object Detection in Adversarial Vision is unique for its diverse content, clear presentation, and overall completeness. It provides a clear, practical, and detailed introduction and advancement of object detection in various representative challenging real-world conditions. Topics and Features: • Offers the first truly comprehensive presentation of aspects of the object detection in degraded and nondegraded environment. • Includes in-depth discussion of various degradation and artifacts, and impact of those artifacts in the real world on solving the object detection problems. • Gives detailed visual examples of applications of object detection in the real world. • Presents a detailed description of popular imaging modalities for object detection adopted by researchers. • Presents the key characteristics of various benchmark datasets in indoor and outdoor environment for solving object detection tasks. • Surveys the complete field of visibility enhancement of degraded scenes, including conventional methods designed for enhancing the degraded scenes as well as the deep architectures. • Discusses techniques for detection of objects in real-world applications. • Contains various hands-on practical examples and a tutorial for solving object detection problems using Python. • Motivates readers to build vision-based systems for solving object detection problems in degraded and nondegraded real-world challenges. The book will be of great interest to a broad audience ranging from researchers and practitioners to graduate and postgraduate students involved in computer vision tasks with respect to object detection in degraded and nondegraded real-world vision problems. |
| computer vision inventory management: Intelligent Systems and Applications in Computer Vision Nitin Mittal, Amit Kant Pandit, Mohamed Abouhawwash, Shubham Mahajan, 2023-11-02 The book comprehensively covers a wide range of evolutionary computer vision methods and applications, feature selection and extraction for training and classification, and metaheuristic algorithms in image processing. It further discusses optimized image segmentation, its analysis, pattern recognition, and object detection. Features: Discusses machine learning-based analytics such as GAN networks, autoencoders, computational imaging, and quantum computing. Covers deep learning algorithms in computer vision. Showcases novel solutions such as multi-resolution analysis in imaging processing, and metaheuristic algorithms for tackling challenges associated with image processing. Highlight optimization problems such as image segmentation and minimized feature design vector. Presents platform and simulation tools for image processing and segmentation. The book aims to get the readers familiar with the fundamentals of computational intelligence as well as the recent advancements in related technologies like smart applications of digital images, and other enabling technologies from the context of image processing and computer vision. It further covers important topics such as image watermarking, steganography, morphological processing, and optimized image segmentation. It will serve as an ideal reference text for senior undergraduate, graduate students, and academic researchers in fields including electrical engineering, electronics, communications engineering, and computer engineering. |
| computer vision inventory management: A Guide for Machine Vision in Quality Control Sheila Anand, L. Priya, 2019-12-23 Machine Vision systems combine image processing with industrial automation. One of the primary areas of application of Machine Vision in the Industry is in the area of Quality Control. Machine vision provides fast, economic and reliable inspection that improves quality as well as business productivity. Building machine vision applications is a challenging task as each application is unique, with its own requirements and desired outcome. A Guide to Machine Vision in Quality Control follows a practitioner’s approach to learning machine vision. The book provides guidance on how to build machine vision systems for quality inspections. Practical applications from the Industry have been discussed to provide a good understanding of usage of machine vision for quality control. Real-world case studies have been used to explain the process of building machine vision solutions. The book offers comprehensive coverage of the essential topics, that includes: Introduction to Machine Vision Fundamentals of Digital Images Discussion of various machine vision system components Digital image processing related to quality control Overview of automation The book can be used by students and academics, as well as by industry professionals, to understand the fundamentals of machine vision. Updates to the on-going technological innovations have been provided with a discussion on emerging trends in machine vision and smart factories of the future. Sheila Anand is a PhD graduate and Professor at Rajalakshmi Engineering College, Chennai, India. She has over three decades of experience in teaching, consultancy and research. She has worked in the software industry and has extensive experience in development of software applications and in systems audit of financial, manufacturing and trading organizations. She guides Ph.D. aspirants and many of her research scholars have since been awarded their doctoral degree. She has published many papers in national and international journals and is a reviewer for several journals of repute. L Priya is a PhD graduate working as Associate Professor and Head, Department of Information Technology at Rajalakshmi Engineering College, Chennai, India. She has nearly two decades of teaching experience and good exposure to consultancy and research. She has delivered many invited talks, presented papers and won several paper awards in International Conferences. She has published several papers in International journals and is a reviewer for SCI indexed journals. Her areas of interest include Machine Vision, Wireless Communication and Machine Learning. |
| computer vision inventory management: Illustrating Digital Innovations Towards Intelligent Fashion Pethuru Raj, |
| computer vision inventory management: Handbook of Research on Thrust Technologies Effect on Image Processing Pandey, Binay Kumar, Pandey, Digvijay, Anand, Rohit, Mane, Deepak S., Nassa, Vinay Kumar, 2023-08-04 Image processing integrates and extracts data from photos for a variety of uses. Applications for image processing are useful in many different disciplines. A few examples include remote sensing, space applications, industrial applications, medical imaging, and military applications. Imaging systems come in many different varieties, including those used for chemical, optical, thermal, medicinal, and molecular imaging. To extract the accurate picture values, scanning methods and statistical analysis must be used for image analysis. Thrust Technologies Effect on Image Processing provides insights into image processing and the technologies that can be used to enhance additional information within an image. The book is also a useful resource for researchers to grow their interest and understanding in the burgeoning fields of image processing. Covering key topics such as image augmentation, artificial intelligence, and cloud computing, this premier reference source is ideal for computer scientists, industry professionals, researchers, academicians, scholars, practitioners, instructors, and students. |
| computer vision inventory management: Computer Vision Technology for Food Quality Evaluation Da-Wen Sun, 2016-04-07 Computer Vision Technology for Food Quality Evaluation, Second Edition continues to be a valuable resource to engineers, researchers, and technologists in research and development, as well as a complete reference to students interested in this rapidly expanding field. This new edition highlights the most recent developments in imaging processing and analysis techniques and methodology, captures cutting-edge developments in computer vision technology, and pinpoints future trends in research and development for food quality and safety evaluation and control. It is a unique reference that provides a deep understanding of the issues of data acquisition and image analysis and offers techniques to solve problems and further develop efficient methods for food quality assessment. - Thoroughly explains what computer vision technology is, what it can do, and how to apply it for food quality evaluation - Includes a wide variety of computer vision techniques and applications to evaluate a wide variety of foods - Describes the pros and cons of different techniques for quality evaluation |
| computer vision inventory management: Machine Vision Fouad Sabry, 2024-05-05 What is Machine Vision The technology and methods that are used to provide imaging-based automatic inspection and analysis for applications such as automatic inspection, process control, and robot guiding, typically in industry, are referred to as machine vision. The term machine vision encompasses a wide range of technologies, including software and hardware items, integrated systems, activities, procedures, and skilled professionals. Unlike computer vision, which is a subfield of computer science, machine vision is a field of systems engineering that might be considered to be different from computer vision. It seeks to combine existing technologies in novel ways and apply them to the solution of problems that are encountered in the real world. This word is the one that is most commonly used for these functions in situations that involve industrial automation; nevertheless, it is also used for these functions in other environments, such as vehicle guiding. How you will benefit (I) Insights, and validations about the following topics: Chapter 1: Machine vision Chapter 2: Computer vision Chapter 3: Thermography Chapter 4: Smart camera Chapter 5: 3D scanning Chapter 6: Mobile mapping Chapter 7: Visual servoing Chapter 8: Visual odometry Chapter 9: Vision-guided robot systems Chapter 10: Optical sorting (II) Answering the public top questions about machine vision. (III) Real world examples for the usage of machine vision in many fields. Who this book is for Professionals, undergraduate and graduate students, enthusiasts, hobbyists, and those who want to go beyond basic knowledge or information for any kind of Machine Vision. |
| computer vision inventory management: Machine Learning Techniques and Industry Applications Srivastava, Pramod Kumar, Yadav, Ashok Kumar, 2024-04-16 In today's rapidly evolving world, the exponential growth of data poses a significant challenge. As data volumes increase, traditional methods of analysis and decision-making become inadequate. This surge in data complexity calls for innovative solutions that efficiently extract meaningful insights. Machine learning has emerged as a powerful tool to address this challenge, offering algorithms and techniques to analyze large datasets and uncover hidden patterns, trends, and correlations. Machine Learning Techniques and Industry Applications demystifies machine learning through detailed explanations, examples, and case studies, making it accessible to a broad audience. Whether you're a student, researcher, or practitioner, this book equips you with the knowledge and skills needed to harness the power of machine learning to address diverse challenges. From e-government to healthcare, cyber-physical systems to agriculture, this book explores how machine learning can drive innovation and sustainable development. |
| computer vision inventory management: Deep Learning Rob Botwright, 101-01-01 Introducing the Ultimate AI Book Bundle: Deep Learning, Computer Vision, Python Machine Learning, and Neural Networks Are you ready to embark on an exhilarating journey into the world of artificial intelligence, deep learning, and computer vision? Look no further! Our carefully curated book bundle, DEEP LEARNING: COMPUTER VISION, PYTHON MACHINE LEARNING AND NEURAL NETWORKS, offers you a comprehensive roadmap to AI mastery. BOOK 1 - DEEP LEARNING DEMYSTIFIED: A BEGINNER'S GUIDE 🚀 Perfect for beginners, this book dismantles the complexities of deep learning. From neural networks to Python programming, you'll build a strong foundation in AI. BOOK 2 - MASTERING COMPUTER VISION WITH DEEP LEARNING 🌟 Dive into the captivating world of computer vision. Unlock the secrets of image processing, convolutional neural networks (CNNs), and object recognition. Harness the power of visual intelligence! BOOK 3 - PYTHON MACHINE LEARNING AND NEURAL NETWORKS: FROM NOVICE TO PRO 📊 Elevate your skills with this intermediate volume. Delve into data preprocessing, supervised and unsupervised learning, and become proficient in training neural networks. BOOK 4 - ADVANCED DEEP LEARNING: CUTTING-EDGE TECHNIQUES AND APPLICATIONS 🔥 Ready to conquer advanced techniques? Learn optimization strategies, tackle common deep learning challenges, and explore real-world applications shaping the future. 🎉 What You'll Gain: · A strong foundation in deep learning · Proficiency in computer vision · Mastery of Python machine learning · Advanced deep learning skills · Real-world application knowledge · Cutting-edge AI insights 📚 Why Choose Our Book Bundle? · Expertly curated content · Beginner to expert progression · Clear explanations and hands-on examples · Comprehensive coverage of AI topics · Practical real-world applications · Stay ahead with emerging AI trends 🌐 Who Should Grab This Bundle? · Beginners eager to start their AI journey · Intermediate learners looking to expand their skill set · Experts seeking advanced deep learning insights · Anyone curious about AI's limitless possibilities 📦 Limited-Time Offer: Get all four books in one bundle and save! Don't miss this chance to accelerate your AI knowledge and skills. 🔒 Secure Your AI Mastery: Click Add to Cart now and embark on an educational adventure that will redefine your understanding of artificial intelligence. Your journey to AI excellence begins here! |
| computer vision inventory management: Robotics, Computer Vision and Intelligent Systems Joaquim Filipe, |
| computer vision inventory management: Emerging Technologies for Business Professionals Nishani Vincent, Amy Igou, 2023-09-26 Embrace emerging technology in your own organization with jargon-free and practical guidance In Emerging Technologies for Business Professionals: A Nontechnical Guide to the Governance and Management of Disruptive Technologies, a team of accomplished accounting systems experts and educators delivers a straightforward and jargon-free management and governance blueprint of emerging technologies ideal for business professionals. In this book you will learn how to use cutting-edge technologies, including AI, analytics, robotic process automation, blockchain, and more to maintain competitive advantage while managing risks. The authors provide real-world examples and case studies of each of the discussed technologies, allowing readers to place the technical details in the context of identifiable business environments. Each chapter offers simple and useful insights in new technology that can be immediately applied by business professionals. Readers will also find: Discussions of a host of new computing technologies, including edge, cloud, and quantum computing Exploration of how the disruptive technologies such as metaverse and non-fungible tokens will impact business operations Easy-to-understand explanations of the latest, most relevant technologies with applications in accounting, marketing, and operations An essential resource for Certified Public Accountants, CPA candidates, and students of accounting and business, Emerging Technologies for Business Professionals will also earn a place in the libraries of anyone interested in adopting emerging technologies in their own organizations. |
| computer vision inventory management: Microsoft Certified: AI-900: Microsoft Azure AI Fundamentals Cybellium, 2024-09-01 Welcome to the forefront of knowledge with Cybellium, your trusted partner in mastering the cutting-edge fields of IT, Artificial Intelligence, Cyber Security, Business, Economics and Science. Designed for professionals, students, and enthusiasts alike, our comprehensive books empower you to stay ahead in a rapidly evolving digital world. * Expert Insights: Our books provide deep, actionable insights that bridge the gap between theory and practical application. * Up-to-Date Content: Stay current with the latest advancements, trends, and best practices in IT, Al, Cybersecurity, Business, Economics and Science. Each guide is regularly updated to reflect the newest developments and challenges. * Comprehensive Coverage: Whether you're a beginner or an advanced learner, Cybellium books cover a wide range of topics, from foundational principles to specialized knowledge, tailored to your level of expertise. Become part of a global network of learners and professionals who trust Cybellium to guide their educational journey. www.cybellium.com |
| computer vision inventory management: Hands-On Reinforcement Learning with Python Sudharsan Ravichandiran, 2018-06-28 A hands-on guide enriched with examples to master deep reinforcement learning algorithms with Python Key Features Your entry point into the world of artificial intelligence using the power of Python An example-rich guide to master various RL and DRL algorithms Explore various state-of-the-art architectures along with math Book Description Reinforcement Learning (RL) is the trending and most promising branch of artificial intelligence. Hands-On Reinforcement learning with Python will help you master not only the basic reinforcement learning algorithms but also the advanced deep reinforcement learning algorithms. The book starts with an introduction to Reinforcement Learning followed by OpenAI Gym, and TensorFlow. You will then explore various RL algorithms and concepts, such as Markov Decision Process, Monte Carlo methods, and dynamic programming, including value and policy iteration. This example-rich guide will introduce you to deep reinforcement learning algorithms, such as Dueling DQN, DRQN, A3C, PPO, and TRPO. You will also learn about imagination-augmented agents, learning from human preference, DQfD, HER, and many more of the recent advancements in reinforcement learning. By the end of the book, you will have all the knowledge and experience needed to implement reinforcement learning and deep reinforcement learning in your projects, and you will be all set to enter the world of artificial intelligence. What you will learn Understand the basics of reinforcement learning methods, algorithms, and elements Train an agent to walk using OpenAI Gym and Tensorflow Understand the Markov Decision Process, Bellman’s optimality, and TD learning Solve multi-armed-bandit problems using various algorithms Master deep learning algorithms, such as RNN, LSTM, and CNN with applications Build intelligent agents using the DRQN algorithm to play the Doom game Teach agents to play the Lunar Lander game using DDPG Train an agent to win a car racing game using dueling DQN Who this book is for If you’re a machine learning developer or deep learning enthusiast interested in artificial intelligence and want to learn about reinforcement learning from scratch, this book is for you. Some knowledge of linear algebra, calculus, and the Python programming language will help you understand the concepts covered in this book. |
| computer vision inventory management: Python Reinforcement Learning Sudharsan Ravichandiran, Sean Saito, Rajalingappaa Shanmugamani, Yang Wenzhuo, 2019-04-18 Apply modern reinforcement learning and deep reinforcement learning methods using Python and its powerful libraries Key FeaturesYour entry point into the world of artificial intelligence using the power of PythonAn example-rich guide to master various RL and DRL algorithmsExplore the power of modern Python libraries to gain confidence in building self-trained applicationsBook Description Reinforcement Learning (RL) is the trending and most promising branch of artificial intelligence. This Learning Path will help you master not only the basic reinforcement learning algorithms but also the advanced deep reinforcement learning algorithms. The Learning Path starts with an introduction to RL followed by OpenAI Gym, and TensorFlow. You will then explore various RL algorithms, such as Markov Decision Process, Monte Carlo methods, and dynamic programming, including value and policy iteration. You'll also work on various datasets including image, text, and video. This example-rich guide will introduce you to deep RL algorithms, such as Dueling DQN, DRQN, A3C, PPO, and TRPO. You will gain experience in several domains, including gaming, image processing, and physical simulations. You'll explore TensorFlow and OpenAI Gym to implement algorithms that also predict stock prices, generate natural language, and even build other neural networks. You will also learn about imagination-augmented agents, learning from human preference, DQfD, HER, and many of the recent advancements in RL. By the end of the Learning Path, you will have all the knowledge and experience needed to implement RL and deep RL in your projects, and you enter the world of artificial intelligence to solve various real-life problems. This Learning Path includes content from the following Packt products: Hands-On Reinforcement Learning with Python by Sudharsan RavichandiranPython Reinforcement Learning Projects by Sean Saito, Yang Wenzhuo, and Rajalingappaa ShanmugamaniWhat you will learnTrain an agent to walk using OpenAI Gym and TensorFlowSolve multi-armed-bandit problems using various algorithmsBuild intelligent agents using the DRQN algorithm to play the Doom gameTeach your agent to play Connect4 using AlphaGo ZeroDefeat Atari arcade games using the value iteration methodDiscover how to deal with discrete and continuous action spaces in various environmentsWho this book is for If you’re an ML/DL enthusiast interested in AI and want to explore RL and deep RL from scratch, this Learning Path is for you. Prior knowledge of linear algebra is expected. |
| computer vision inventory management: Machine Learning Maria Johnsen, 2024-07-06 Machine learning has revolutionized industries, from healthcare to entertainment, by enhancing how we understand and interact with data. Despite its prevalence, mastering this field requires both theoretical knowledge and practical skills. This book bridges that gap, starting with foundational concepts and essential mathematics, then advancing through a wide range of algorithms and techniques. It covers supervised and unsupervised learning, neural networks, deep learning, and reinforcement learning, with clear explanations and practical examples. Real-world applications are highlighted through scenarios and case studies, demonstrating how to solve specific problems with machine learning. You'll find hands-on guides to popular tools and libraries like Python, Scikit-Learn, TensorFlow, Keras, and PyTorch, enabling you to build, evaluate, and deploy models effectively. The book explores cutting-edge topics like quantum machine learning and explainable AI, keeping you updated on the latest trends. Detailed case studies and capstone projects provide practical experience, guiding you through the entire machine learning process. This book, a labor of love born from extensive research and passion, aims to make machine learning accessible and engaging. Machine learning is about curiosity, creativity, and the pursuit of knowledge. Explore, experiment, and enjoy the journey. Thank you for choosing this book. I am excited to be part of your machine learning adventure and look forward to the incredible things you will achieve. |
| computer vision inventory management: Inside Nvidia: Jensen Huang's Vision for Artificial Intelligence Alistair Maxwell, PhD, Daniel D. Lee, 2024-08-06 Inside Nvidia: Jensen Huang's Vision for Artificial Intelligence by Dr. Alistair Maxwell, PhD, is a comprehensive exploration of Nvidia's journey from a fledgling graphics card company to a global leader in AI technology. Through meticulous research and insightful analysis, Dr. Maxwell delves into the strategic decisions and visionary leadership of Jensen Huang, the co-founder and CEO of Nvidia. This book provides readers with an in-depth understanding of how Nvidia has revolutionized industries ranging from gaming to healthcare with its cutting-edge GPUs and AI advancements. It covers the company's strategic acquisitions, partnerships, and innovations that have positioned it at the forefront of the AI revolution. Dr. Maxwell also explains complex AI concepts, making them accessible to the average reader, and explores the ethical considerations and future prospects of AI technology. From the architecture of Nvidia’s GPUs to their applications in autonomous vehicles, healthcare, and beyond, Inside Nvidia is a must-read for anyone interested in the intersection of technology, business, and artificial intelligence. Published by AGI Publishing, this book is not only a detailed account of Nvidia’s past and present but also a visionary look at the future of AI and its potential to transform our world. Available now on Google Play, this book is perfect for technology enthusiasts, business leaders, and anyone curious about the future of AI. Dive into the fascinating story of Nvidia and discover how Jensen Huang's vision is shaping the future of artificial intelligence. |
| computer vision inventory management: A Handbook on Board's Preparedness on Transformative Technonolgies Institute of Directors , This handbook aims to equip you with the necessary knowledge and tools to effectively navigate digital transformation and leverage transformative technologies for sustainable business growth. It explores key concepts, emerging trends, and best practices that will enable boards to adapt to the digital age and make informed decisions. From understanding the fundamentals of transformative technologies to exploring their implications on governance, strategy, risk management, and innovation, this handbook provides practical insights and case studies. |
| computer vision inventory management: Computer Vision and Internet of Things Lavanya Sharma, Mukesh Carpenter, 2022-05-19 Computer Vision and Internet of Things: Technologies and Applications explores the utilization of Internet of Things (IoT) with computer vision and its underlying technologies in different applications areas. Using a series of present and future applications – including business insights, indoor-outdoor securities, smart grids, human detection and tracking, intelligent traffic monitoring, e-health departments, and medical imaging – this book focuses on providing a detailed description of the utilization of IoT with computer vision and its underlying technologies in critical application areas, such as smart grids, emergency departments, intelligent traffic cams, insurance, and the automotive industry. Key Features • Covers the challenging issues related to sensors, detection, and tracking of moving objects with solutions to handle relevant challenges • Describes the latest technological advances in IoT and computer vision with their implementations • Combines image processing and analysis into a unified framework to understand both IOT and computer vision applications • Explores mining and tracking of motion-based object data, such as trajectory prediction and prediction of a particular location of object data, and their critical applications • Provides novel solutions for medical imaging (skin lesion detection, cancer detection, enhancement techniques for MRI images, and automated disease prediction) This book is primarily aimed at graduates and researchers working in the areas of IoT, computer vision, big data, cloud computing, and remote sensing. It is also an ideal resource for IT professionals and technology developers. |
| computer vision inventory management: Modern Management Science Practices in the Age of AI Jermsittiparsert, Kittisak, Phongkraphan, Nattharawee, Lekhavichit, Nuchnapha, 2024-08-26 Management has always been a multifaceted and continuously changing aspect of the business world. Today, with the introduction of revolutionary technology, working environments, and new individual attitudes, it is essential to understand more information than ever. A comprehensive knowledge of the interworking of accounting, behavior, decision making, strategy, data, marketing, and revenue management is a must for any manager to act as efficiently and effectively as possible. Modern Management Science Practices in the Age of AI offers a thorough and interdisciplinary exploration of management, addressing key aspects such as challenge resolution, strategic planning, execution, and performance measurement. It refines and transforms organizational operations across various sectors including public, private, and civil society. Drawing on insights from global scholars, researchers, and practitioners, the volume provides a rich collection of contemporary knowledge that is invaluable for both academics and practitioners. By integrating these diverse fields, the book equips both researchers and organizational managers with the tools needed to adapt and thrive in a rapidly evolving environment. |
| computer vision inventory management: Artificial Intelligence Dr. V. Deepa, Dr. Jeyanthi, Mrs. P.R.Sukanya Sridevi, Augustin Kirubakaran, 2024-09-27 Artificial Intelligence delves into the transformative world of AI, exploring its foundational theories, practical applications, and ethical implications. Covering core topics like machine learning, neural networks, and natural language processing, the book offers a comprehensive view of AI's potential to reshape industries, enhance decision-making, and drive innovation. With discussions on challenges, advancements, and future trends, this resource serves as an essential guide for students, professionals, and enthusiasts eager to understand and engage with the dynamic field of artificial intelligence. |
| computer vision inventory management: Intelligent Systems for Smart Cities Anand J. Kulkarni, Naoufel Cheikhrouhou, 2024-01-02 This book presents the select proceedings of the 2nd International Conference on Intelligent Systems and Applications 2023. The theme of this conference is ‘Intelligent Systems for Smart Cities'. It covers the topics of intelligent systems in multiple aspects such as healthcare, supply chain and logistics, smart homes and smart structures, banking and finance, a sustainable environment, social media and cyber security, crime prevention, and disaster management. The book will be useful for researchers and professionals interested in the broad field of artificial intelligence and machine learning. |
| computer vision inventory management: Emerging Digital Media Ecologies Toija Cinque, 2024-11-18 Emerging Digital Media Ecologies: The Concept of Medialogy investigates the profound ways in which digital media reshapes our cultural, socio-technological, political, and natural landscapes. Through interdisciplinary empirical and creative case studies, the book defines and illuminates the nuances of medialogy, emphasising the often-underestimated impact of emerging technologies across interactive education, data gathering, visual-data representations, and creative practice. It explores the intersection of the natural and technological worlds, contextualising our use of natural resources against climate change and sustainable economies. Divided into two parts, the book delves into the theoretical underpinnings of digital media ecologies and their practical applications. Part 1 traces the evolution of media technologies, examining their environmental impact and the foundational approaches to understanding media’s complex interconnections. Part 2 focuses on contemporary issues such as hyperpersonalised media, digital literacy, and the transformative power of Indigenous media narratives. Additionally, the monograph explores the revolutionary role of Artificial Intelligence (AI) and large language models like ChatGPT-4o and those that follow in shaping our digital future. It investigates how AI transforms creative practices, data processing, and communication, contributing to the formation of new media ecologies. The ethical implications, commodification, identity formation, and the impact of AI-driven technologies on everyday life are critically examined, offering insights into the future of human–technology interactions. This book is a crucial reference for scholars, practitioners, and students in digital humanities, media studies, environmental humanities, and anyone interested in the cultural implications of emerging digital technologies and their impact on our environment and society. |
| computer vision inventory management: Active Machine Learning with Python Margaux Masson-Forsythe, 2024-03-29 Use active machine learning with Python to improve the accuracy of predictive models, streamline the data analysis process, and adapt to evolving data trends, fostering innovation and progress across diverse fields Key Features Learn how to implement a pipeline for optimal model creation from large datasets and at lower costs Gain profound insights within your data while achieving greater efficiency and speed Apply your knowledge to real-world use cases and solve complex ML problems Purchase of the print or Kindle book includes a free PDF eBook Book DescriptionBuilding accurate machine learning models requires quality data—lots of it. However, for most teams, assembling massive datasets is time-consuming, expensive, or downright impossible. Led by Margaux Masson-Forsythe, a seasoned ML engineer and advocate for surgical data science and climate AI advancements, this hands-on guide to active machine learning demonstrates how to train robust models with just a fraction of the data using Python's powerful active learning tools. You’ll master the fundamental techniques of active learning, such as membership query synthesis, stream-based sampling, and pool-based sampling and gain insights for designing and implementing active learning algorithms with query strategy and Human-in-the-Loop frameworks. Exploring various active machine learning techniques, you’ll learn how to enhance the performance of computer vision models like image classification, object detection, and semantic segmentation and delve into a machine AL method for selecting the most informative frames for labeling large videos, addressing duplicated data. You’ll also assess the effectiveness and efficiency of active machine learning systems through performance evaluation. By the end of the book, you’ll be able to enhance your active learning projects by leveraging Python libraries, frameworks, and commonly used tools.What you will learn Master the fundamentals of active machine learning Understand query strategies for optimal model training with minimal data Tackle class imbalance, concept drift, and other data challenges Evaluate and analyze active learning model performance Integrate active learning libraries into workflows effectively Optimize workflows for human labelers Explore the finest active learning tools available today Who this book is for Ideal for data scientists and ML engineers aiming to maximize model performance while minimizing costly data labeling, this book is your guide to optimizing ML workflows and prioritizing quality over quantity. Whether you’re a technical practitioner or team lead, you’ll benefit from the proven methods presented in this book to slash data requirements and iterate faster. Basic Python proficiency and familiarity with machine learning concepts such as datasets and convolutional neural networks is all you need to get started. |
| computer vision inventory management: Artificial Intelligence for Business Transforming Strategies for Success Sam Morgan, 2024-11-12 Discover how to leverage technology with Artificial Intelligence for Business Transforming Strategies for Success. This comprehensive guide explores the impact of artificial intelligence in business environments, providing actionable insights on implementing AI strategies to enhance operational efficiency and drive business transformation. Learn about the power of machine learning, automation, and data-driven decisions that can reshape your organization's future. This book is your essential resource for navigating the evolving landscape of AI in business. |
| computer vision inventory management: Machine Learning and It's Techniques Dr. Lakshmi Anusha Kothamasu, 2024-07-29 The book Machine Learning and Its Techniques provides a thorough examination of the fundamental approaches and uses of machine learning. The book is designed to take readers from fundamental ideas to more complex subjects, guaranteeing a deep comprehension of the material. Neural networks, deep learning, reinforcement learning, and both supervised and unsupervised learning are important subjects. The theoretical ideas in each chapter are followed by real-world examples and learning-enhancement activities. Common machine learning problems including overfitting, underfitting, and model assessment are also covered in the book. A comprehensive perspective of the discipline is provided by giving particular attention to the ethical issues and potential directions of machine learning. Readers will have acquired the information and abilities needed to use machine learning methods in an ethical and successful manner by the time they finish this book. This thorough tutorial is perfect for anybody who wants to learn more about machine learning and use it in practical situations. |
| computer vision inventory management: Artificial Intelligence-Enabled Digital Twin for Smart Manufacturing Amit Kumar Tyagi, Shrikant Tiwari, Senthil Kumar Arumugam, Avinash Kumar Sharma, 2024-10-15 An essential book on the applications of AI and digital twin technology in the smart manufacturing sector. In the rapidly evolving landscape of modern manufacturing, the integration of cutting-edge technologies has become imperative for businesses to remain competitive and adaptive. Among these technologies, Artificial Intelligence (AI) stands out as a transformative force, revolutionizing traditional manufacturing processes and making the way for the era of smart manufacturing. At the heart of this technological revolution lies the concept of the Digital Twin—an innovative approach that bridges the physical and digital realms of manufacturing. By creating a virtual representation of physical assets, processes, and systems, organizations can gain unprecedented insights, optimize operations, and enhance decision-making capabilities. This timely book explores the convergence of AI and Digital Twin technologies to empower smart manufacturing initiatives. Through a comprehensive examination of principles, methodologies, and practical applications, it explains the transformative potential of AI-enabled Digital Twins across various facets of the manufacturing lifecycle. From design and prototyping to production and maintenance, AI-enabled Digital Twins offer multifaceted advantages that redefine traditional paradigms. By leveraging AI algorithms for data analysis, predictive modeling, and autonomous optimization, manufacturers can achieve unparalleled levels of efficiency, quality, and agility. This book explains how AI enhances the capabilities of Digital Twins by creating a powerful tool that can optimize production processes, improve product quality, and streamline operations. Note that the Digital Twin in this context is a virtual representation of a physical manufacturing system, including machines, processes, and products. It continuously collects real-time data from sensors and other sources, allowing it to mirror the physical system’s behavior and performance. What sets this Digital Twin apart is the incorporation of AI algorithms and machine learning techniques that enable it to analyze and predict outcomes, recommend improvements, and autonomously make adjustments to enhance manufacturing efficiency. This book outlines essential elements, like real-time monitoring of machines, predictive analytics of machines and data, optimization of the resources, quality control of the product, resource management, decision support (timely or quickly accurate decisions). Moreover, this book elucidates the symbiotic relationship between AI and Digital Twins, highlighting how AI augments the capabilities of Digital Twins by infusing them with intelligence, adaptability, and autonomy. Hence, this book promises to enhance competitiveness, reduce operational costs, and facilitate innovation in the manufacturing industry. By harnessing AI’s capabilities in conjunction with Digital Twins, manufacturers can achieve a more agile and responsive production environment, ultimately driving the evolution of smart factories and Industry 4.0/5.0. Audience This book has a wide audience in computer science, artificial intelligence, and manufacturing engineering, as well as engineers in a variety of industrial manufacturing industries. It will also appeal to economists and policymakers working on the circular economy, clean tech investors, industrial decision-makers, and environmental professionals. |
| computer vision inventory management: Computer Vision and Imaging in Intelligent Transportation Systems Robert P. Loce, Raja Bala, Mohan Trivedi, 2017-11-08 Acts as single source reference providing readers with an overview of how computer vision can contribute to the different applications in the field of road transportation This book presents a survey of computer vision techniques related to three key broad problems in the roadway transportation domain: safety, efficiency, and law enforcement. The individual chapters present significant applications within those problem domains, each presented in a tutorial manner, describing the motivation for and benefits of the application, and a description of the state of the art. Key features: Surveys the applications of computer vision techniques to road transportation system for the purposes of improving safety and efficiency and to assist law enforcement. Offers a timely discussion as computer vision is reaching a point of being useful in the field of transportation systems. Available as an enhanced eBook with video demonstrations to further explain the concepts discussed in the book, as well as links to publically available software and data sets for testing and algorithm development. The book will benefit the many researchers, engineers and practitioners of computer vision, digital imaging, automotive and civil engineering working in intelligent transportation systems. Given the breadth of topics covered, the text will present the reader with new and yet unconceived possibilities for application within their communities. |
| computer vision inventory management: Integrating Metaheuristics in Computer Vision for Real-World Optimization Problems Shubham Mahajan, Kapil Joshi, Amit Kant Pandit, Nitish Pathak, 2024-08-01 A comprehensive book providing high-quality research addressing challenges in theoretical and application aspects of soft computing and machine learning in image processing and computer vision. Researchers are working to create new algorithms that combine the methods provided by CI approaches to solve the problems of image processing and computer vision such as image size, noise, illumination, and security. The 19 chapters in this book examine computational intelligence (CI) approaches as alternative solutions for automatic computer vision and image processing systems in a wide range of applications, using machine learning and soft computing. Applications highlighted in the book include: diagnostic and therapeutic techniques for ischemic stroke, object detection, tracking face detection and recognition; computational-based strategies for drug repositioning and improving performance with feature selection, extraction, and learning; methods capable of retrieving photometric and geometric transformed images; concepts of trading the cryptocurrency market based on smart price action strategies; comparative evaluation and prediction of exoplanets using machine learning methods; the risk of using failure rate with the help of MTTF and MTBF to calculate reliability; a detailed description of various techniques using edge detection algorithms; machine learning in smart houses; the strengths and limitations of swarm intelligence and computation; how to use bidirectional LSTM for heart arrhythmia detection; a comprehensive study of content-based image-retrieval techniques for feature extraction; machine learning approaches to understanding angiogenesis; handwritten image enhancement based on neutroscopic-fuzzy. Audience The book has been designed for researchers, engineers, graduate, and post-graduate students wanting to learn more about the theoretical and application aspects of soft computing and machine learning in image processing and computer vision. |
| computer vision inventory management: Industry Automation: The Technologies, Platforms and Use Cases Pethuru Raj, Abhishek Kumar, Ananth Kumar, Neha Singhal, 2024-08-23 This book details cutting-edge technologies, versatile tools, adaptive processes, integrated platforms, and best practices of digitized systems. With the faster maturity and stability of digitization and digitalization technologies, all kinds of physical, mechanical, and electrical systems in our everyday environments (homes, hotels, hospitals, manufacturing floors, etc.) have become digitized systems. Such technology has empowered systems to gain the power to join and contribute to fulfilling the goals of modern computing. Such digitized entities assist in producing and deploying hugely complicated yet sophisticated context-aware services and applications. The other principal contribution is capturing environmental data in real time and enabling local data processing to bring forth actionable insights. This facilitates insight-driven decisions and deeds. Precisely speaking, the aspects of real-time knowledge discovery and dissemination enable the creation and delivery of real-time and real-world features and functionalities. All industrial artifacts are being digitized, connected and empowered to be cognitive in their operations, offerings and outputs. By smartly leveraging a dazzling array of digital technologies and tools, the interaction and collaboration with human experts becomes hugely simplified and speeded up considerably. Such cognition-enabled industrial machineries, equipment, appliances, assembly lines, robots, vehicles, drones, and other assets collectively provide an intelligent environment to envisage and realize state-of-the-art industry 4.0 and 5.0 applications. Every industrial process gets optimized and automated to produce next-generation products to ensure customer delight, to explore fresh avenues to enhance revenues and to embark on higher productivity. In addition, there are chapters illustrating industrial use cases, infrastructure optimization, technology assimilation, and AI-powered data analytics towards industry automation. |
| computer vision inventory management: AI at Work Abdullah Bin Siddique, 2024-11-10 |
| computer vision inventory management: Mastering Deep Learning with TensorFlow: From Fundamentals to Real-World Deployment Peter Jones, 2024-10-11 Explore the realm of artificial intelligence with Mastering Deep Learning with TensorFlow: From Fundamentals to Real-World Deployment. This all-encompassing guide provides an in-depth understanding of AI, machine learning, and deep learning, powered by TensorFlow—Google's leading AI framework. Whether you're a beginner starting your AI journey or a professional looking to elevate your expertise in AI model deployment, this book is tailored to meet your needs. Covering crucial topics like neural network design, convolutional and recurrent neural networks, natural language processing, and computer vision, it offers a robust introduction to TensorFlow and its AI applications. Through hands-on examples and a focus on practical solutions, you'll learn how to apply TensorFlow to solve real-world challenges. From theoretical foundations to deployment techniques, Mastering Deep Learning with TensorFlow takes you through every step, preparing you to build, fine-tune, and deploy advanced AI models. By the end, you’ll be ready to harness TensorFlow’s full potential, making strides in the rapidly evolving field of artificial intelligence. This book is an indispensable resource for anyone eager to engage with or advance in AI. |
| computer vision inventory management: Smart Technologies in Data Science and Communication Sanjoy Kumar Saha, Paul S. Pang, Debnath Bhattacharyya, 2021-06-07 This book features high-quality, peer-reviewed research papers presented at the Fourth International Conference on Smart Technologies in Data Science and Communication (SMART-DSC 2021), held in Koneru Lakshmaiah Education Foundation, Guntur, Andhra Pradesh, India, on 18–19 February 2021. It includes innovative and novel contributions in the areas of data analytics, communication, and soft computing. |
| computer vision inventory management: Revolutionizing Supply Chains Through Digital Transformation Benatiya Andaloussi, Manal, 2024-11-08 In the modern business landscape, the confluence of digital technologies with supply chain management (SCM) has ushered in an era of unprecedented change and opportunity. The concept of SCM, once rooted in traditional logistics and operational efficiency, has evolved into a sophisticated, technology-driven discipline. It is essential to leverage advanced tools to optimize supply chain processes, enhance transparency, and drive more informed decision-making. These innovations not only improve efficiency but also offer businesses a competitive edge in an increasingly complex global market. Revolutionizing Supply Chains Through Digital Transformation offers a comprehensive examination of how digital innovations are not only transforming supply chains but are also fundamentally redefining the value creation process across industries. It delves into the integration of technologies reshaping the way businesses manage their supply chains. Covering topics such as 5G technology, decarbonized transportation, and waste management, this book is an excellent resource for academicians, researchers, supply chain and operations management professionals, executives, managers, decision makers, and graduate and postgraduate students. |
| computer vision inventory management: Machine Learning Algorithms and Techniques Krishna Bonagiri, 2024-06-21 Machine Learning Algorithms and Techniques the concepts, popular algorithms, and essential techniques of machine learning. A comprehensive covering supervised, unsupervised, and reinforcement learning methods while exploring key algorithms like decision trees, neural networks, clustering, and more. Practical applications and examples bring each algorithm to life, helping readers understand how these models are used to solve real-world problems. Designed for both beginners and experienced practitioners, this book is an ideal guide for mastering the fundamentals and applications of machine learning. |
| computer vision inventory management: Underwater Computer Vision Fouad Sabry, 2024-04-28 What is Underwater Computer Vision Underwater computer vision is a subfield of computer vision. In recent years, with the development of underwater vehicles, the need to be able to record and process huge amounts of information has become increasingly important. Applications range from inspection of underwater structures for the offshore industry to the identification and counting of fishes for biological research. However, no matter how big the impact of this technology can be to industry and research, it still is in a very early stage of development compared to traditional computer vision. One reason for this is that, the moment the camera goes into the water, a whole new set of challenges appear. On one hand, cameras have to be made waterproof, marine corrosion deteriorates materials quickly and access and modifications to experimental setups are costly, both in time and resources. On the other hand, the physical properties of the water make light behave differently, changing the appearance of a same object with variations of depth, organic material, currents, temperature etc. How you will benefit (I) Insights, and validations about the following topics: Chapter 1: Underwater computer vision Chapter 2: Computer vision Chapter 3: Hydrographic survey Chapter 4: Autonomous underwater vehicle Chapter 5: Monterey Bay Aquarium Research Institute Chapter 6: Unmanned underwater vehicle Chapter 7: Noise reduction Chapter 8: Underwater vision Chapter 9: Video post-processing Chapter 10: Image quality (II) Answering the public top questions about underwater computer vision. (III) Real world examples for the usage of underwater computer vision in many fields. Who this book is for Professionals, undergraduate and graduate students, enthusiasts, hobbyists, and those who want to go beyond basic knowledge or information for any kind of Underwater Computer Vision. |
Computer - Wikipedia
A computer is a machine that can be programmed to automatically carry out sequences of arithmetic or logical operations (computation). Modern digital electronic computers can …
Computer | Definition, History, Operating Systems, & Facts
A computer is a programmable device for processing, storing, and displaying information. Learn more in this article about modern digital electronic computers and their design, constituent …
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What is a computer? A computer is an electronic device that manipulates information, or data. It has the ability to store, retrieve, and process data. You may already know that you can use a …
What is a Computer? (Definition & Meaning) - Webopedia
Oct 9, 2024 · A computer is a programmable machine that responds to specific instructions and uses hardware and software to perform tasks. Different types of computers, including …
Computer - Simple English Wikipedia, the free encyclopedia
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What is Computer? Definition, Characteristics and Classification
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Computer - Wikipedia
A computer is a machine that can be programmed to automatically carry out sequences of arithmetic or logical operations (computation). Modern digital electronic computers can …
Computer | Definition, History, Operating Systems, & Facts
A computer is a programmable device for processing, storing, and displaying information. Learn more in this article about modern digital electronic computers and their design, constituent …
What is a Computer?
Feb 6, 2025 · What is a Computer? A computer is a programmable device that stores, retrieves, and processes data. The term "computer" was originally given to humans (human computers) …
Micro Center - Computer & Electronics Retailer - Shop Now
Shop Micro Center for electronics, PCs, laptops, Apple products, and much more. Enjoy in-store pickup, top deals, and expert same-day tech support.
What is a Computer? - GeeksforGeeks
Apr 7, 2025 · A computer is an electronic device that processes, stores, and executes instructions to perform tasks. It includes key components such as the CPU (Central Processing Unit), RAM …
Computer Basics: What is a Computer? - GCFGlobal.org
What is a computer? A computer is an electronic device that manipulates information, or data. It has the ability to store, retrieve, and process data. You may already know that you can use a …
What is a Computer? (Definition & Meaning) - Webopedia
Oct 9, 2024 · A computer is a programmable machine that responds to specific instructions and uses hardware and software to perform tasks. Different types of computers, including …
Computer - Simple English Wikipedia, the free encyclopedia
A computer is a machine that uses electronics to input, process, store, and output data. Data is information such as numbers, words, and lists. Input of data means to read information from a …
Laptop & Desktop Computers - Staples
Buy the computer that fits your exact needs. Choose from laptops, desktops PCs, notebooks, and accessories. Invest in a quality computer for work or personal use.
What is Computer? Definition, Characteristics and Classification
Aug 7, 2024 · A computer is an electronic device wherein we need to input raw data to be processed with a set of programs to produce a desirable output. Computers have the ability to …
