A Guide To Convolutional Neural Networks For Computer Vision
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A Guide To Convolutional Neural Networks For Computer Vision
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Author : Salman Khan
language : en
Publisher: Morgan & Claypool Publishers
Release Date : 2018-02-13
A Guide To Convolutional Neural Networks For Computer Vision written by Salman Khan and has been published by Morgan & Claypool Publishers this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-02-13 with Computers categories.
Computer vision has become increasingly important and effective in recent years due to its wide-ranging applications in areas as diverse as smart surveillance and monitoring, health and medicine, sports and recreation, robotics, drones, and self-driving cars. Visual recognition tasks, such as image classification, localization, and detection, are the core building blocks of many of these applications, and recent developments in Convolutional Neural Networks (CNNs) have led to outstanding performance in these state-of-the-art visual recognition tasks and systems. As a result, CNNs now form the crux of deep learning algorithms in computer vision. This self-contained guide will benefit those who seek to both understand the theory behind CNNs and to gain hands-on experience on the application of CNNs in computer vision. It provides a comprehensive introduction to CNNs starting with the essential concepts behind neural networks: training, regularization, and optimization of CNNs. The book also discusses a wide range of loss functions, network layers, and popular CNN architectures, reviews the different techniques for the evaluation of CNNs, and presents some popular CNN tools and libraries that are commonly used in computer vision. Further, this text describes and discusses case studies that are related to the application of CNN in computer vision, including image classification, object detection, semantic segmentation, scene understanding, and image generation. This book is ideal for undergraduate and graduate students, as no prior background knowledge in the field is required to follow the material, as well as new researchers, developers, engineers, and practitioners who are interested in gaining a quick understanding of CNN models.
A Guide To Convolutional Neural Networks For Computer Vision
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Author : Salman Khan
language : en
Publisher: Springer Nature
Release Date : 2022-06-01
A Guide To Convolutional Neural Networks For Computer Vision written by Salman Khan and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-06-01 with Computers categories.
Computer vision has become increasingly important and effective in recent years due to its wide-ranging applications in areas as diverse as smart surveillance and monitoring, health and medicine, sports and recreation, robotics, drones, and self-driving cars. Visual recognition tasks, such as image classification, localization, and detection, are the core building blocks of many of these applications, and recent developments in Convolutional Neural Networks (CNNs) have led to outstanding performance in these state-of-the-art visual recognition tasks and systems. As a result, CNNs now form the crux of deep learning algorithms in computer vision. This self-contained guide will benefit those who seek to both understand the theory behind CNNs and to gain hands-on experience on the application of CNNs in computer vision. It provides a comprehensive introduction to CNNs starting with the essential concepts behind neural networks: training, regularization, and optimization of CNNs.The book also discusses a wide range of loss functions, network layers, and popular CNN architectures, reviews the different techniques for the evaluation of CNNs, and presents some popular CNN tools and libraries that are commonly used in computer vision. Further, this text describes and discusses case studies that are related to the application of CNN in computer vision, including image classification, object detection, semantic segmentation, scene understanding, and image generation. This book is ideal for undergraduate and graduate students, as no prior background knowledge in the field is required to follow the material, as well as new researchers, developers, engineers, and practitioners who are interested in gaining a quick understanding of CNN models.
Guide To Convolutional Neural Networks
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Author : Hamed Habibi Aghdam
language : en
Publisher: Springer
Release Date : 2017-05-17
Guide To Convolutional Neural Networks written by Hamed Habibi Aghdam and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017-05-17 with Computers categories.
This must-read text/reference introduces the fundamental concepts of convolutional neural networks (ConvNets), offering practical guidance on using libraries to implement ConvNets in applications of traffic sign detection and classification. The work presents techniques for optimizing the computational efficiency of ConvNets, as well as visualization techniques to better understand the underlying processes. The proposed models are also thoroughly evaluated from different perspectives, using exploratory and quantitative analysis. Topics and features: explains the fundamental concepts behind training linear classifiers and feature learning; discusses the wide range of loss functions for training binary and multi-class classifiers; illustrates how to derive ConvNets from fully connected neural networks, and reviews different techniques for evaluating neural networks; presents a practical library for implementing ConvNets, explaining how to use a Python interface for the library to create and assess neural networks; describes two real-world examples of the detection and classification of traffic signs using deep learning methods; examines a range of varied techniques for visualizing neural networks, using a Python interface; provides self-study exercises at the end of each chapter, in addition to a helpful glossary, with relevant Python scripts supplied at an associated website. This self-contained guide will benefit those who seek to both understand the theory behind deep learning, and to gain hands-on experience in implementing ConvNets in practice. As no prior background knowledge in the field is required to follow the material, the book is ideal for all students of computer vision and machine learning, and will also be of great interest to practitioners working on autonomous cars and advanced driver assistance systems.
Computer Vision Eccv 2020
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Author : Andrea Vedaldi
language : en
Publisher: Springer Nature
Release Date : 2020-11-20
Computer Vision Eccv 2020 written by Andrea Vedaldi and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-11-20 with Computers categories.
The 30-volume set, comprising the LNCS books 12346 until 12375, constitutes the refereed proceedings of the 16th European Conference on Computer Vision, ECCV 2020, which was planned to be held in Glasgow, UK, during August 23-28, 2020. The conference was held virtually due to the COVID-19 pandemic. The 1360 revised papers presented in these proceedings were carefully reviewed and selected from a total of 5025 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.
Convolutional Neural Networks In Python
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Author : Frank Millstein
language : en
Publisher: Frank Millstein
Release Date : 2020-07-06
Convolutional Neural Networks In Python written by Frank Millstein and has been published by Frank Millstein this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-07-06 with Computers categories.
Convolutional Neural Networks in Python This book covers the basics behind Convolutional Neural Networks by introducing you to this complex world of deep learning and artificial neural networks in a simple and easy to understand way. It is perfect for any beginner out there looking forward to learning more about this machine learning field. This book is all about how to use convolutional neural networks for various image, object and other common classification problems in Python. Here, we also take a deeper look into various Keras layer used for building CNNs we take a look at different activation functions and much more, which will eventually lead you to creating highly accurate models able of performing great task results on various image classification, object classification and other problems. Therefore, at the end of the book, you will have a better insight into this world, thus you will be more than prepared to deal with more complex and challenging tasks on your own. Here Is a Preview of What You’ll Learn In This Book… Convolutional neural networks structure How convolutional neural networks actually work Convolutional neural networks applications The importance of convolution operator Different convolutional neural networks layers and their importance Arrangement of spatial parameters How and when to use stride and zero-padding Method of parameter sharing Matrix multiplication and its importance Pooling and dense layers Introducing non-linearity relu activation function How to train your convolutional neural network models using backpropagation How and why to apply dropout CNN model training process How to build a convolutional neural network Generating predictions and calculating loss functions How to train and evaluate your MNIST classifier How to build a simple image classification CNN And much, much more! Get this book NOW and learn more about Convolutional Neural Networks in Python!
Convolutional Neural Networks In Visual Computing
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Author : Ragav Venkatesan
language : en
Publisher: CRC Press
Release Date : 2017-10-23
Convolutional Neural Networks In Visual Computing written by Ragav Venkatesan and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017-10-23 with Computers categories.
This book covers the fundamentals in designing and deploying techniques using deep architectures. It is intended to serve as a beginner's guide to engineers or students who want to have a quick start on learning and/or building deep learning systems. This book provides a good theoretical and practical understanding and a complete toolkit of basic information and knowledge required to understand and build convolutional neural networks (CNN) from scratch. The book focuses explicitly on convolutional neural networks, filtering out other material that co-occur in many deep learning books on CNN topics.
Computer Vision
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Author : Mrinal Kanti Bhowmik
language : en
Publisher: CRC Press
Release Date : 2024-03-07
Computer Vision written by Mrinal Kanti Bhowmik and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-03-07 with Computers categories.
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.
Intelligent Systems And Networks
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Author : Thi Dieu Linh Nguyen
language : en
Publisher: Springer Nature
Release Date : 2023-08-19
Intelligent Systems And Networks written by Thi Dieu Linh Nguyen and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-08-19 with Computers categories.
This book presents Proceedings of the International Conference on Intelligent Systems and Networks (ICISN 2023), held at Hanoi in Vietnam. It includes peer reviewed high impact research manuscripts, that highlight the work based on Intelligent System and Networks. The book presents ongoing research outcomes, results and cutting edge works which are of importance to professionals and academics/researchers. It covers topics such as Computational Intelligence in Language and Speech Processing; Software development methods; Wireless Communications and Signal Processing; IoT and Sensor Embedded Systems ; etc.
Proceedings Of The Future Technologies Conference Ftc 2022 Volume 1
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Author : Kohei Arai
language : en
Publisher: Springer Nature
Release Date : 2022-10-12
Proceedings Of The Future Technologies Conference Ftc 2022 Volume 1 written by Kohei Arai and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-10-12 with Technology & Engineering categories.
The seventh Future Technologies Conference 2022 was organized in a hybrid mode. It received a total of 511 submissions from learned scholars, academicians, engineers, scientists and students across many countries. The papers included the wide arena of studies like Computing, Artificial Intelligence, Machine Vision, Ambient Intelligence and Security and their jaw- breaking application to the real world. After a double-blind peer review process 177 submissions have been selected to be included in these proceedings. One of the prominent contributions of this conference is the confluence of distinguished researchers who not only enthralled us by their priceless studies but also paved way for future area of research. The papers provide amicable solutions to many vexing problems across diverse fields. They also are a window to the future world which is completely governed by technology and its multiple applications. We hope that the readers find this volume interesting and inspiring and render their enthusiastic support towards it.
Proceedings Of Fifth International Conference On Computer And Communication Technologies
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Author : B. Rama Devi
language : en
Publisher: Springer Nature
Release Date : 2024-02-29
Proceedings Of Fifth International Conference On Computer And Communication Technologies written by B. Rama Devi and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-02-29 with Computers categories.
This book is a compilation of high-quality scientific papers presented at the 5th International Conference on Computer & Communication Technologies (IC3T 2023). The book covers cutting-edge technologies and applications of soft computing, artificial intelligence and communication. In addition, a variety of further topics are discussed, which include data mining, machine intelligence, fuzzy computing, sensor networks, signal and image processing, human–computer interaction, and web intelligence.