| contrastive language image pre training: Computer Vision – ECCV 2024 Aleš Leonardis, |
| contrastive language image pre training: Computer Vision – ECCV 2022 Shai Avidan, Gabriel Brostow, Moustapha Cissé, Giovanni Maria Farinella, Tal Hassner, 2022-10-31 The 39-volume set, comprising the LNCS books 13661 until 13699, constitutes the refereed proceedings of the 17th European Conference on Computer Vision, ECCV 2022, held in Tel Aviv, Israel, during October 23–27, 2022. The 1645 papers presented in these proceedings were carefully reviewed and selected from a total of 5804 submissions. The papers deal with topics such as computer vision; machine learning; deep neural networks; reinforcement learning; object recognition; image classification; image processing; object detection; semantic segmentation; human pose estimation; 3d reconstruction; stereo vision; computational photography; neural networks; image coding; image reconstruction; object recognition; motion estimation. |
| contrastive language image pre training: Computer Vision – ECCV 2024 Aleš Leonardis, |
| contrastive language image pre training: Proceedings of the 9th Italian Conference on Computational Linguistics CLiC-it 2023 AA.VV., 2024-06-26 The ninth edition of the Italian Conference on Computational Linguistics (CLiC-it 2023) was held from 30th November to 2nd December 2023 at Ca' Foscari University of Venice, in the beautiful venue of the Auditorium Santa Margherita - Emanuele Severino. After the edition of 2020, which was organized in fully virtual mode due to the health emergency related to Covid-19, and CLiC-it 2021, which was held in hybrid mode, with CLiC-it 2023 we are back to a fully in-presence conference. Overall, almost 210 participants registered to the conference, confirming that the community is eager to meet in person and to enjoy both the scientific and social events together with the colleagues. |
| contrastive language image pre training: Medical Image Computing and Computer Assisted Intervention – MICCAI 2023 Hayit Greenspan, Anant Madabhushi, Parvin Mousavi, Septimiu Salcudean, James Duncan, Tanveer Syeda-Mahmood, Russell Taylor, 2023-09-30 The ten-volume set LNCS 14220, 14221, 14222, 14223, 14224, 14225, 14226, 14227, 14228, and 14229 constitutes the refereed proceedings of the 26th International Conference on Medical Image Computing and Computer-Assisted Intervention, MICCAI 2023, which was held in Vancouver, Canada, in October 2023. The 730 revised full papers presented were carefully reviewed and selected from a total of 2250 submissions. The papers are organized in the following topical sections: Part I: Machine learning with limited supervision and machine learning – transfer learning; Part II: Machine learning – learning strategies; machine learning – explainability, bias, and uncertainty; Part III: Machine learning – explainability, bias and uncertainty; image segmentation; Part IV: Image segmentation; Part V: Computer-aided diagnosis; Part VI: Computer-aided diagnosis; computational pathology; Part VII: Clinical applications – abdomen; clinical applications – breast; clinical applications – cardiac; clinical applications – dermatology; clinical applications – fetal imaging; clinical applications – lung; clinical applications – musculoskeletal; clinical applications – oncology; clinical applications – ophthalmology; clinical applications – vascular; Part VIII: Clinical applications – neuroimaging; microscopy; Part IX: Image-guided intervention, surgical planning, and data science; Part X: Image reconstruction and image registration. |
| contrastive language image pre training: Modern Computer Vision with PyTorch V Kishore Ayyadevara, Yeshwanth Reddy, 2024-06-10 The definitive computer vision book is back, featuring the latest neural network architectures and an exploration of foundation and diffusion models Purchase of the print or Kindle book includes a free eBook in PDF format Key Features Understand the inner workings of various neural network architectures and their implementation, including image classification, object detection, segmentation, generative adversarial networks, transformers, and diffusion models Build solutions for real-world computer vision problems using PyTorch All the code files are available on GitHub and can be run on Google Colab Book DescriptionWhether you are a beginner or are looking to progress in your computer vision career, this book guides you through the fundamentals of neural networks (NNs) and PyTorch and how to implement state-of-the-art architectures for real-world tasks. The second edition of Modern Computer Vision with PyTorch is fully updated to explain and provide practical examples of the latest multimodal models, CLIP, and Stable Diffusion. You’ll discover best practices for working with images, tweaking hyperparameters, and moving models into production. As you progress, you'll implement various use cases for facial keypoint recognition, multi-object detection, segmentation, and human pose detection. This book provides a solid foundation in image generation as you explore different GAN architectures. You’ll leverage transformer-based architectures like ViT, TrOCR, BLIP2, and LayoutLM to perform various real-world tasks and build a diffusion model from scratch. Additionally, you’ll utilize foundation models' capabilities to perform zero-shot object detection and image segmentation. Finally, you’ll learn best practices for deploying a model to production. By the end of this deep learning book, you'll confidently leverage modern NN architectures to solve real-world computer vision problems.What you will learn Get to grips with various transformer-based architectures for computer vision, CLIP, Segment-Anything, and Stable Diffusion, and test their applications, such as in-painting and pose transfer Combine CV with NLP to perform OCR, key-value extraction from document images, visual question-answering, and generative AI tasks Implement multi-object detection and segmentation Leverage foundation models to perform object detection and segmentation without any training data points Learn best practices for moving a model to production Who this book is for This book is for beginners to PyTorch and intermediate-level machine learning practitioners who want to learn computer vision techniques using deep learning and PyTorch. It's useful for those just getting started with neural networks, as it will enable readers to learn from real-world use cases accompanied by notebooks on GitHub. Basic knowledge of the Python programming language and ML is all you need to get started with this book. For more experienced computer vision scientists, this book takes you through more advanced models in the latter part of the book. |
| contrastive language image pre training: 18th International Conference on Soft Computing Models in Industrial and Environmental Applications (SOCO 2023) Pablo García Bringas, Hilde Pérez García, Francisco Javier Martínez de Pisón, Francisco Martínez Álvarez, Alicia Troncoso Lora, Álvaro Herrero, José Luis Calvo Rolle, Héctor Quintián, Emilio Corchado, 2023-10-01 This book of Advances in Intelligent and Soft Computing contains accepted papers presented at SOCO 2023 conference held in the beautiful and historic city of Salamanca (Spain) in September 2023. Soft computing represents a collection or set of computational techniques in machine learning, computer science, and some engineering disciplines, which investigate, simulate, and analyze very complex issues and phenomena. After a through peer-review process, the 18th SOCO 2023 International Program Committee selected 61 papers which are published in these conference proceedings and represents an acceptance rate of 60%. In this relevant edition, a particular emphasis was put on the organization of special sessions. Seven special sessions were organized related to relevant topics such as: Time Series Forecasting in Industrial and Environmental Applications, Technological Foundations and Advanced Applications of Drone Systems, Soft Computing Methods in Manufacturing and Management Systems, Efficiency and Explainability in Machine Learning and Soft Computing, Machine Learning and Computer Vision in Industry 4.0, Genetic and Evolutionary Computation in Real World and Industry, and Soft Computing and Hard Computing for a Data Science Process Model. The selection of papers was extremely rigorous to maintain the high quality of the conference. We want to thank the members of the Program Committees for their hard work during the reviewing process. This is a crucial process for creating a high-standard conference; the SOCO conference would not exist without their help. |
| contrastive language image pre training: Pretrain Vision and Large Language Models in Python Emily Webber, Andrea Olgiati, 2023-05-31 Master the art of training vision and large language models with conceptual fundaments and industry-expert guidance. Learn about AWS services and design patterns, with relevant coding examples Key Features Learn to develop, train, tune, and apply foundation models with optimized end-to-end pipelines Explore large-scale distributed training for models and datasets with AWS and SageMaker examples Evaluate, deploy, and operationalize your custom models with bias detection and pipeline monitoring Book Description Foundation models have forever changed machine learning. From BERT to ChatGPT, CLIP to Stable Diffusion, when billions of parameters are combined with large datasets and hundreds to thousands of GPUs, the result is nothing short of record-breaking. The recommendations, advice, and code samples in this book will help you pretrain and fine-tune your own foundation models from scratch on AWS and Amazon SageMaker, while applying them to hundreds of use cases across your organization. With advice from seasoned AWS and machine learning expert Emily Webber, this book helps you learn everything you need to go from project ideation to dataset preparation, training, evaluation, and deployment for large language, vision, and multimodal models. With step-by-step explanations of essential concepts and practical examples, you'll go from mastering the concept of pretraining to preparing your dataset and model, configuring your environment, training, fine-tuning, evaluating, deploying, and optimizing your foundation models. You will learn how to apply the scaling laws to distributing your model and dataset over multiple GPUs, remove bias, achieve high throughput, and build deployment pipelines. By the end of this book, you'll be well equipped to embark on your own project to pretrain and fine-tune the foundation models of the future. What you will learn Find the right use cases and datasets for pretraining and fine-tuning Prepare for large-scale training with custom accelerators and GPUs Configure environments on AWS and SageMaker to maximize performance Select hyperparameters based on your model and constraints Distribute your model and dataset using many types of parallelism Avoid pitfalls with job restarts, intermittent health checks, and more Evaluate your model with quantitative and qualitative insights Deploy your models with runtime improvements and monitoring pipelines Who this book is for If you're a machine learning researcher or enthusiast who wants to start a foundation modelling project, this book is for you. Applied scientists, data scientists, machine learning engineers, solution architects, product managers, and students will all benefit from this book. Intermediate Python is a must, along with introductory concepts of cloud computing. A strong understanding of deep learning fundamentals is needed, while advanced topics will be explained. The content covers advanced machine learning and cloud techniques, explaining them in an actionable, easy-to-understand way. |
| contrastive language image pre training: Intelligent Computing for Sustainable Development S. Satheeskumaran, |
| contrastive language image pre training: Deep Learning at Scale Suneeta Mall, 2024-06-18 Bringing a deep-learning project into production at scale is quite challenging. To successfully scale your project, a foundational understanding of full stack deep learning, including the knowledge that lies at the intersection of hardware, software, data, and algorithms, is required. This book illustrates complex concepts of full stack deep learning and reinforces them through hands-on exercises to arm you with tools and techniques to scale your project. A scaling effort is only beneficial when it's effective and efficient. To that end, this guide explains the intricate concepts and techniques that will help you scale effectively and efficiently. You'll gain a thorough understanding of: How data flows through the deep-learning network and the role the computation graphs play in building your model How accelerated computing speeds up your training and how best you can utilize the resources at your disposal How to train your model using distributed training paradigms, i.e., data, model, and pipeline parallelism How to leverage PyTorch ecosystems in conjunction with NVIDIA libraries and Triton to scale your model training Debugging, monitoring, and investigating the undesirable bottlenecks that slow down your model training How to expedite the training lifecycle and streamline your feedback loop to iterate model development A set of data tricks and techniques and how to apply them to scale your training model How to select the right tools and techniques for your deep-learning project Options for managing the compute infrastructure when running at scale |
| contrastive language image pre training: Gpt-4 for Developers OSWALD. CAMPESATO, 2023-12-22 This resource is designed to bridge the gap between theoretical understanding and practical application, making it a useful tool for software developers, data scientists, AI researchers, and tech enthusiasts interested in harnessing the power of GPT-4 in Python environments. The book contains an assortment of Python 3.x code samples that were generated by ChatGPT and GPT-4. Chapter 1 provides an overview of ChatGPT and GPT-4, followed by a chapter which contains Python 3.x code samples for solving various programming tasks in Python. Chapter 3 contains code samples for data visualization, and Chapter 4 contains code samples for linear regression. The final chapter covers visualization with Gen AI (Generative AI) and DALL-E. Companion files with source code and figures are available for downloading. FEATURES Offers an all-encompassing view of ChatGPT and GPT-4, from basics to advanced topics, including functionalities, capabilities, and limitations Contains Python 3.x code samples demonstrating the application of GPT-4 in real-world scenarios Provides a forward-looking perspective on Generative AI and its integration with data visualization and DALL-E Includes companion files with source code, data sets, and figures |
| contrastive language image pre training: Document Analysis and Recognition - ICDAR 2024 Elisa H. Barney Smith, |
| contrastive language image pre training: Modern Electronics Devices and Communication Systems Rajeev Agrawal, Chandramani Kishore Singh, Ayush Goyal, Dinesh Kumar Singh, 2023-02-18 This book presents select and peer-reviewed proceedings of the International Conference on Smart Communication and Imaging Systems (MEDCOM 2021). The contents explore the recent technological advances in the field of next-generation electronics devices and communication systems. The topics include the design and development of smart, secure, and reliable future communication networks; satellite, radar, and microwave techniques for intelligent communication. The book also covers methods and applications of GIS and remote sensing; medical image analysis and its applications in smart health. This book can be useful for students, researchers, and professionals working in the field of communication systems and image processing. |
| contrastive language image pre training: Industrial Networks and Intelligent Systems Nguyen-Son Vo, |
| contrastive language image pre training: Document Analysis Systems Giorgos Sfikas, |
| contrastive language image pre training: Experimental IR Meets Multilinguality, Multimodality, and Interaction Cross-Language Evaluation Forum. Conference, 2024 The two volume set LNCS 14958 + 14959 constitutes the proceedings of the 15th International Conference of the CLEF Association, CLEF 2024, held in Grenoble, France, during September 9–12, 2024. The proceedings contain 11 conference papers; 6 best of CLEF 2023 Labs' papers, and 14 Lab overview papers accepted from 45 submissions. In addition an overview paper on the CLEF activities in the last 25 years is included. The CLEF conference and labs of the evaluation forum deal with topics in information access from different perspectives, in any modality and language, focusing on experimental information retrieval (IR). . |
| contrastive language image pre training: Database Systems for Advanced Applications Xin Wang, Maria Luisa Sapino, Wook-Shin Han, Amr El Abbadi, Gill Dobbie, Zhiyong Feng, Yingxiao Shao, Hongzhi Yin, 2023-04-14 The four-volume set LNCS 13943, 13944, 13945 and 13946 constitutes the proceedings of the 28th International Conference on Database Systems for Advanced Applications, DASFAA 2023, held in April 2023 in Tianjin, China. The total of 125 full papers, along with 66 short papers, are presented together in this four-volume set was carefully reviewed and selected from 652 submissions. Additionally, 15 industrial papers, 15 demo papers and 4 PhD consortium papers are included. The conference presents papers on subjects such as model, graph, learning, performance, knowledge, time, recommendation, representation, attention, prediction, and network. |
| contrastive language image pre training: Medical Image Computing and Computer Assisted Intervention – MICCAI 2024 Marius George Linguraru, |
| contrastive language image pre training: Similarity Search and Applications Edgar Chávez, |
| contrastive language image pre training: Computer Vision – ECCV 2022 Workshops Leonid Karlinsky, Tomer Michaeli, Ko Nishino, 2023-02-13 The 8-volume set, comprising the LNCS books 13801 until 13809, constitutes the refereed proceedings of 38 out of the 60 workshops held at the 17th European Conference on Computer Vision, ECCV 2022. The conference took place in Tel Aviv, Israel, during October 23-27, 2022; the workshops were held hybrid or online. The 367 full papers included in this volume set were carefully reviewed and selected for inclusion in the ECCV 2022 workshop proceedings. They were organized in individual parts as follows: Part I: W01 - AI for Space; W02 - Vision for Art; W03 - Adversarial Robustness in the Real World; W04 - Autonomous Vehicle Vision Part II: W05 - Learning With Limited and Imperfect Data; W06 - Advances in Image Manipulation; Part III: W07 - Medical Computer Vision; W08 - Computer Vision for Metaverse; W09 - Self-Supervised Learning: What Is Next?; Part IV: W10 - Self-Supervised Learning for Next-Generation Industry-Level Autonomous Driving; W11 - ISIC Skin Image Analysis; W12 - Cross-Modal Human-Robot Interaction; W13 - Text in Everything; W14 - BioImage Computing; W15 - Visual Object-Oriented Learning Meets Interaction: Discovery, Representations, and Applications; W16 - AI for Creative Video Editing and Understanding; W17 - Visual Inductive Priors for Data-Efficient Deep Learning; W18 - Mobile Intelligent Photography and Imaging; Part V: W19 - People Analysis: From Face, Body and Fashion to 3D Virtual Avatars; W20 - Safe Artificial Intelligence for Automated Driving; W21 - Real-World Surveillance: Applications and Challenges; W22 - Affective Behavior Analysis In-the-Wild; Part VI: W23 - Visual Perception for Navigation in Human Environments: The JackRabbot Human Body Pose Dataset and Benchmark; W24 - Distributed Smart Cameras; W25 - Causality in Vision; W26 - In-Vehicle Sensing and Monitorization; W27 - Assistive Computer Vision and Robotics; W28 - Computational Aspects of Deep Learning; Part VII: W29 - Computer Vision for Civil and Infrastructure Engineering; W30 - AI-Enabled Medical Image Analysis: Digital Pathology and Radiology/COVID19; W31 - Compositional and Multimodal Perception; Part VIII: W32 - Uncertainty Quantification for Computer Vision; W33 - Recovering 6D Object Pose; W34 - Drawings and Abstract Imagery: Representation and Analysis; W35 - Sign Language Understanding; W36 - A Challenge for Out-of-Distribution Generalization in Computer Vision; W37 - Vision With Biased or Scarce Data; W38 - Visual Object Tracking Challenge. |
| contrastive language image pre training: Beyond AI Ken Huang, Yang Wang, Feng Zhu, Xi Chen, Chunxiao Xing, 2024-01-27 This book explores the transformative potential of ChatGPT, Web3, and their impact on productivity and various industries. It delves into Generative AI (GenAI) and its representative platform ChatGPT, their synergy with Web3, and how they can revolutionize business operations. It covers the potential impact surpassing prior industrial revolutions. After providing an overview of GenAI, ChatGPT, and Web3, it investigates business applications in various industries and areas, such as product management, finance, real estate, gaming, and government, highlighting value creation and operational revolution through their integration. It also explores their impact on content generation, customer service, personalization, and data analysis and examines how the technologies can enhance content quality, customer experiences, sales, revenue, and resource efficiency. Moreover, it addresses security, privacy, and ethics concerns, emphasizing the responsible implementation of ChatGPT and Web3. Written by experts in this field, this book is aimed at business leaders, entrepreneurs, students, investors, and professionals who are seeking insights into ChatGPT, ChatGPT Plug-in, GPT-based autonomous agents, and the integration of Gen AI and Web3 in business applications. |
| contrastive language image pre training: Medical Image Computing and Computer Assisted Intervention – MICCAI 2024 Marius George Linguraru, |
| contrastive language image pre training: Neural Information Processing Biao Luo, Long Cheng, Zheng-Guang Wu, Hongyi Li, Chaojie Li, 2023-11-26 The nine-volume set constitutes the refereed proceedings of the 30th International Conference on Neural Information Processing, ICONIP 2023, held in Changsha, China, in November 2023. The 1274 papers presented in the proceedings set were carefully reviewed and selected from 652 submissions. The ICONIP conference aims to provide a leading international forum for researchers, scientists, and industry professionals who are working in neuroscience, neural networks, deep learning, and related fields to share their new ideas, progress, and achievements. |
| contrastive language image pre training: Generative AI Martin Musiol, 2023-01-08 An engaging and essential discussion of generative artificial intelligence In Generative AI: Navigating the Course to the Artificial General Intelligence Future, celebrated author Martin Musiol—founder and CEO of generativeAI.net and GenAI Lead for Europe at Infosys—delivers an incisive and one-of-a-kind discussion of the current capabilities, future potential, and inner workings of generative artificial intelligence. In the book, you'll explore the short but eventful history of generative artificial intelligence, what it's achieved so far, and how it's likely to evolve in the future. You'll also get a peek at how emerging technologies are converging to create exciting new possibilities in the GenAI space. Musiol analyzes complex and foundational topics in generative AI, breaking them down into straightforward and easy-to-understand pieces. You'll also find: Bold predictions about the future emergence of Artificial General Intelligence via the merging of current AI models Fascinating explorations of the ethical implications of AI, its potential downsides, and the possible rewards Insightful commentary on Autonomous AI Agents and how AI assistants will become integral to daily life in professional and private contexts Perfect for anyone interested in the intersection of ethics, technology, business, and society—and for entrepreneurs looking to take advantage of this tech revolution—Generative AI offers an intuitive, comprehensive discussion of this fascinating new technology. |
| contrastive language image pre training: MultiMedia Modeling Duc-Tien Dang-Nguyen, Cathal Gurrin, Martha Larson, Alan F. Smeaton, Stevan Rudinac, Minh-Son Dao, Christoph Trattner, Phoebe Chen, 2023-03-28 The two-volume set LNCS 13833 and LNCS 13834 constitutes the proceedings of the 29th International Conference on MultiMedia Modeling, MMM 2023, which took place in Bergen, Norway, during January 9-12, 2023. The 86 papers presented in these proceedings were carefully reviewed and selected from a total of 267 submissions. They focus on topics related to multimedia content analysis; multimedia signal processing and communications; and multimedia applications and services. |
| contrastive language image pre training: Probabilistic Machine Learning Kevin P. Murphy, 2022-03-01 A detailed and up-to-date introduction to machine learning, presented through the unifying lens of probabilistic modeling and Bayesian decision theory. This book offers a detailed and up-to-date introduction to machine learning (including deep learning) through the unifying lens of probabilistic modeling and Bayesian decision theory. The book covers mathematical background (including linear algebra and optimization), basic supervised learning (including linear and logistic regression and deep neural networks), as well as more advanced topics (including transfer learning and unsupervised learning). End-of-chapter exercises allow students to apply what they have learned, and an appendix covers notation. Probabilistic Machine Learning grew out of the author’s 2012 book, Machine Learning: A Probabilistic Perspective. More than just a simple update, this is a completely new book that reflects the dramatic developments in the field since 2012, most notably deep learning. In addition, the new book is accompanied by online Python code, using libraries such as scikit-learn, JAX, PyTorch, and Tensorflow, which can be used to reproduce nearly all the figures; this code can be run inside a web browser using cloud-based notebooks, and provides a practical complement to the theoretical topics discussed in the book. This introductory text will be followed by a sequel that covers more advanced topics, taking the same probabilistic approach. |
| contrastive language image pre training: Artificial Intelligence in Music, Sound, Art and Design Colin Johnson, Nereida Rodríguez-Fernández, Sérgio M. Rebelo, 2023-03-31 This book constitutes the refereed proceedings of the 12th European Conference on Artificial Intelligence in Music, Sound, Art and Design, EvoMUSART 2023, held as part of Evo* 2023, in April 2023, co-located with the Evo* 2023 events, EvoCOP, EvoApplications, and EuroGP. The 20 full papers and 7 short papers presented in this book were carefully reviewed and selected from 55 submissions. They cover a wide range of topics and application areas of artificial intelligence, including generative approaches to music and visual art, deep learning, and architecture. |
| contrastive language image pre training: Pattern Recognition and Computer Vision Qingshan Liu, Hanzi Wang, Zhanyu Ma, Weishi Zheng, Hongbin Zha, Xilin Chen, Liang Wang, Rongrong Ji, 2023-12-23 The 13-volume set LNCS 14425-14437 constitutes the refereed proceedings of the 6th Chinese Conference on Pattern Recognition and Computer Vision, PRCV 2023, held in Xiamen, China, during October 13–15, 2023. The 532 full papers presented in these volumes were selected from 1420 submissions. The papers have been organized in the following topical sections: Action Recognition, Multi-Modal Information Processing, 3D Vision and Reconstruction, Character Recognition, Fundamental Theory of Computer Vision, Machine Learning, Vision Problems in Robotics, Autonomous Driving, Pattern Classification and Cluster Analysis, Performance Evaluation and Benchmarks, Remote Sensing Image Interpretation, Biometric Recognition, Face Recognition and Pose Recognition, Structural Pattern Recognition, Computational Photography, Sensing and Display Technology, Video Analysis and Understanding, Vision Applications and Systems, Document Analysis and Recognition, Feature Extraction and Feature Selection, Multimedia Analysis and Reasoning, Optimization and Learning methods, Neural Network and Deep Learning, Low-Level Vision and Image Processing, Object Detection, Tracking and Identification, Medical Image Processing and Analysis. |
| contrastive language image pre training: Transformer, BERT, and GPT3 Oswald Campesato, 2023-11-21 This book provides a comprehensive group of topics covering the details of the Transformer architecture, BERT models, and the GPT series, including GPT-3 and GPT-4. Spanning across ten chapters, it begins with foundational concepts such as the attention mechanism, then tokenization techniques, explores the nuances of Transformer and BERT architectures, and culminates in advanced topics related to the latest in the GPT series, including ChatGPT. Key chapters provide insights into the evolution and significance of attention in deep learning, the intricacies of the Transformer architecture, a two-part exploration of the BERT family, and hands-on guidance on working with GPT-3. The concluding chapters present an overview of ChatGPT, GPT-4, and visualization using generative AI. In addition to the primary topics, the book also covers influential AI organizations such as DeepMind, OpenAI, Cohere, Hugging Face, and more. Readers will gain a comprehensive understanding of the current landscape of NLP models, their underlying architectures, and practical applications. Features companion files with numerous code samples and figures from the book. FEATURES: Provides a comprehensive group of topics covering the details of the Transformer architecture, BERT models, and the GPT series, including GPT-3 and GPT-4. Features companion files with numerous code samples and figures from the book. |
| contrastive language image pre training: Web Information Systems and Applications Long Yuan, Shiyu Yang, Ruixuan Li, Evangelos Kanoulas, Xiang Zhao, 2023-09-08 This book constitutes the proceedings of the 20th International Conference on Web Information Systems and Applications, WISA 2023, held in Chengdu, China, in September 2023. The 43 full papers and 9 short papers presented in this book were carefully reviewed and selected from 213 submissions. The papers are grouped in topical sections on Data Mining and Knowledge Discovery, Recommender Systems, Natural Language Processing, Security, Privacy and Trust, Blockchain, Parallel and Distributed Systems and Database for Artificial Intelligence.. |
| contrastive language image pre training: E-Business. New Challenges and Opportunities for Digital-Enabled Intelligent Future Yiliu Paul Tu, |
| contrastive language image pre training: Deep Learning Research Applications for Natural Language Processing Ashok Kumar, L., Karthika Renuka, Dhanaraj, Geetha, S., 2022-12-09 Humans have the most advanced method of communication, which is known as natural language. While humans can use computers to send voice and text messages to each other, computers do not innately know how to process natural language. In recent years, deep learning has primarily transformed the perspectives of a variety of fields in artificial intelligence (AI), including speech, vision, and natural language processing (NLP). The extensive success of deep learning in a wide variety of applications has served as a benchmark for the many downstream tasks in AI. The field of computer vision has taken great leaps in recent years and surpassed humans in tasks related to detecting and labeling objects thanks to advances in deep learning and neural networks. Deep Learning Research Applications for Natural Language Processing explains the concepts and state-of-the-art research in the fields of NLP, speech, and computer vision. It provides insights into using the tools and libraries in Python for real-world applications. Covering topics such as deep learning algorithms, neural networks, and advanced prediction, this premier reference source is an excellent resource for computational linguists, software engineers, IT managers, computer scientists, students and faculty of higher education, libraries, researchers, and academicians. |
| contrastive language image pre training: Artificial Intelligence in HCI Helmut Degen, Stavroula Ntoa, 2022-05-14 This book constitutes the refereed proceedings of the Third International Conference on Artificial Intelligence in HCI, AI-HCI 2022, which was held as part of HCI International 2022 and took place virtually during June 26 – July 1, 2022. A total of 1271 papers and 275 posters included in the 39 HCII 2022 proceedings volumes. AI-HCI 2022 includes a total of 39 papers; they are grouped thematically as follows: Human-Centered AI; Explainable and Trustworthy AI; UX Design and Evaluation of AI-Enabled Systems; AI Applications in HCI. |
| contrastive language image pre training: Artificial Intelligence and Soft Computing Leszek Rutkowski, Rafał Scherer, Marcin Korytkowski, Witold Pedrycz, Ryszard Tadeusiewicz, Jacek M. Zurada, 2023-09-13 The two-volume set LNAI 14125 and 14126 constitutes the refereed conference proceedings of the 22nd International Conference on Artificial Intelligence and Soft Computing, ICAISC 2023, held in Zakopane, Poland, during June 18–22, 2023. The 84 revised full papers presented in these proceedings were carefully reviewed and selected from 175 submissions. The papers are organized in the following topical sections: Part I: Neural Networks and Their Applications; Evolutionary Algorithms and Their Applications; and Artificial Intelligence in Modeling and Simulation. Part II: Computer Vision, Image and Speech Analysis; Various Problems of Artificial Intelligence; Bioinformatics, Biometrics and Medical Applications; and Data Mining and Pateern Classification. |
| contrastive language image pre training: Foundation Models for General Medical AI Zhongying Deng, |
| contrastive language image pre training: Large Language Models Oswald Campesato, 2024-09-17 This book begins with an overview of the Generative AI landscape, distinguishing it from conversational AI and shedding light on the roles of key players like DeepMind and OpenAI. It then reviews the intricacies of ChatGPT, GPT-4, Meta AI, Claude 3, and Gemini, examining their capabilities, strengths, and competitors. Readers will also gain insights into the BERT family of LLMs, including ALBERT, DistilBERT, and XLNet, and how these models have revolutionized natural language processing. Further, the book covers prompt engineering techniques, essential for optimizing the outputs of AI models, and addresses the challenges of working with LLMs, including the phenomenon of hallucinations and the nuances of fine-tuning these advanced models. Designed for software developers, AI researchers, and technology enthusiasts with a foundational understanding of AI, this book offers both theoretical insights and practical code examples in Python. Companion files with code, figures, and datasets are available for downloading from the publisher. FEATURES: Covers in-depth explanations of foundational and advanced LLM concepts, including BERT, GPT-4, and prompt engineering Uses practical Python code samples in leveraging LLM functionalities effectively Discusses future trends, ethical considerations, and the evolving landscape of AI technologies Includes companion files with code, datasets, and images from the book -- available from the publisher for downloading (with proof of purchase) |
| contrastive language image pre training: Industry 6.0 C Kishor Kumar Reddy, Srinath Doss, Lavanya Pamulaparty, Kari Lippert, Ruchi Doshi, 2024-10-16 What are the means to create a paradigm shift from conventional to intelligent companies? Industry 6.0: Technology, Practices, Challenges and Applications shows how integrating Industry 6.0 technology with data creates a framework for that shift. The book discusses the limitations, pitfalls, and open research questions in Industry 6.0, as well as the most recent advances, architectures, frameworks, applications, and novel practices, methods, and techniques. These are vital for resolving intelligent Internet of Things issues. There is a special focus on sustainable growth, humanization and environmentally friendly intelligent system applications, and an emphasis on the latest innovations in intelligent systems in classical machine learning, deep learning, Internet of Things (IoT), Industrial Internet of Things (IIoT), blockchain, knowledge representation, knowledge management, big data, and natural language processing (NLP). Features: Presents the latest trends in the fields of intelligent systems, machine intelligence, deep learning, and Industrial Internet of Things for smart environments. Discusses securing the mobile ad hoc network (MANET) by detecting the Intrusions using CSO and XGBoost model. Highlights the methods of smart things in collaborative autonomous fleets and platforms for integrating applications across different business and industry domains. Focuses on intelligent process manufacturing, automation using robotics, development of robotic appliances, and smart manufacturing. Covers data-driven agriculture, crop disease prediction, drip irrigation systems, pesticide and fertilizer sprinkling using the Industrial Internet of Things, and water estimation systems. With many contemporary articles from both scientists and practitioners working in many fields where intelligent systems and the IIoT can break new ground, the text is assembled to aim at a readership that includes researchers, statisticians, practitioners, scientists, and developers. |
| contrastive language image pre training: Machine Learning in Medical Imaging Xuanang Xu, |
| contrastive language image pre training: Proceedings of the 2024 2nd International Conference on Image, Algorithms and Artificial Intelligence Yulin Wang, 2024 |
| contrastive language image pre training: Foundations of Intelligent Systems Michelangelo Ceci, Sergio Flesca, Elio Masciari, Giuseppe Manco, Zbigniew W. Raś, 2022-09-26 This book constitutes the proceedings of the 26th International Symposium on Foundations of Intelligent Systems, ISMIS 2022, held in Cosenza, Italy, in October 2022. The 31 regular papers, 11 short papers and 4 industrial papers presented in this volume were carefully reviewed and selected from 71 submissions. They were organized in topical sections as follows: Social Media and Recommendation; Natural Language Processing; Explainability; Intelligent Systems; Classification and Clustering; Complex Data; Medical Applications; Industrial Applications. |
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Is there a tag to turn off caching in all browsers?
The list is just examples of different techniques, it's not for direct insertion. If copied, the second would overwrite the first and the fourth would overwrite the third because of the http-equiv …
regex - Adding ?nocache=1 to every url (including the assets like ...
Jul 12, 2016 · But what I would like to do is to apply ?nocache=1 to every URL related to the site (including the assets like style.css) so that I get the non cached version of the files.
http - What is the difference between no-cache and no-store in …
I don't find get the practical difference between Cache-Control:no-store and Cache-Control:no-cache. As far as I know, no-store means that no cache device is allowed to cache that …
How to force Docker for a clean build of an image
Feb 24, 2016 · Use the --no-cache option in Docker to force a clean build of an image.
Disable browser cache for entire ASP.NET website
Jul 21, 2009 · I am looking for a method to disable the browser cache for an entire ASP.NET MVC Website I found the following method: …
Difference between no-cache and must-revalidate for Cache …
Jun 1, 2022 · @Anshul No, must-revalidate and no-cache have different meaning for fresh responses: If a cached response is fresh (i.e, the response hasn't expired), must-revalidate will …
How do we control web page caching, across all browsers?
Our investigations have shown us that not all browsers respect the HTTP cache directives in a uniform manner. For security reasons we do not want certain pages in our application to be …
Why both no-cache and no-store should be used in HTTP response?
no-store should not be necessary in normal situations, and in some cases can harm speed and usability. It was intended as a privacy measure: it tells browsers and caches that the response …
caching - No cache in Node.js server - Stack Overflow
Dec 7, 2013 · Ok, even if you aren't using express, what essentially needed is to set the nocache headers. I'm adding the headers in a reusable middleware, otherwise you can set those …
How to disable webpage caching in ExpressJS + NodeJS?
By default, my browser caches webpages of my ExpressJS app. This is causing a problem to my login system (users not logged in can open old cached pages of logged in users). How do I …
