Applied Computer Vision And Soft Computing With Interpretable Ai
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Applied Computer Vision And Soft Computing With Interpretable Ai
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Author : Swati V. Shinde
language : en
Publisher: CRC Press
Release Date : 2023-10-05
Applied Computer Vision And Soft Computing With Interpretable Ai written by Swati V. Shinde and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-10-05 with Computers categories.
This reference text presents the knowledge base of computer vision and soft computing techniques with their applications for sustainable developments. Features: Covers a variety of deep learning architectures useful for computer vision tasks Demonstrates the use of different soft computing techniques and their applications for different computer vision tasks Highlights the unified strengths of hybrid techniques based on deep learning and soft computing taken together that give the interpretable, adaptive, and optimized solution to a given problem Addresses the different issues and further research opportunities in computer vision and soft computing Describes all the concepts with practical examples and case studies with appropriate performance measures that validate the applicability of the respective technique to a certain domain Considers recent real word problems and the prospective solutions to these problems This book will be useful to researchers, students, faculty, and industry personnel who are eager to explore the power of deep learning and soft computing for different computer vision tasks.
Applied Computer Vision And Soft Computing With Interpretable Ai
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Author : Swati V. Shinde
language : en
Publisher: CRC Press
Release Date : 2023-10-12
Applied Computer Vision And Soft Computing With Interpretable Ai written by Swati V. Shinde and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-10-12 with Computers categories.
This reference text presents the knowledge base of computer vision and soft computing techniques with their applications for sustainable developments. Features: ∙ Covers a variety of deep learning architectures useful for computer vision tasks. ∙ Demonstrates the use of different soft computing techniques and their applications for different computer vision tasks. ∙ Highlights the unified strengths of hybrid techniques based on deep learning and soft computing taken together that give the interpretable, adaptive, and optimized solution to a given problem. ∙ Addresses the different issues and further research opportunities in computer vision and soft computing. ∙ Describes all the concepts with practical examples and case studies with appropriate performance measures that validate the applicability of the respective technique to a certain domain. ∙ Considers recent real word problems and the prospective solutions to these problems. This book will be useful to researchers, students, faculty, and industry personnel who are eager to explore the power of deep learning and soft computing for different computer vision tasks.
Computer Recognition Systems 4
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Author : Robert Burduk
language : en
Publisher: Springer Science & Business Media
Release Date : 2011-04-21
Computer Recognition Systems 4 written by Robert Burduk and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2011-04-21 with Technology & Engineering categories.
The computer recognition systems are nowadays one of the most promising directions in artificial intelligence. This book is the most comprehensive study of this field. It contains a collection of 78 carefully selected articles contributed by experts of pattern recognition. It reports on current research with respect to both methodology and applications. In particular, it includes the following sections: Biometrics, Features, learning and classifiers, Image processing and computer vision, Knowledge acquisition based on reasoning methods Medical applications, Miscellaneous applications, This book is a great reference tool for scientists who deal with the problems of designing computer pattern recognition systems. Its target readers can be as well researchers as students of computer science, artificial intelligence or robotics.
Computer Recognition Systems 3
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Author : Marek Kurzynski
language : en
Publisher: Springer Science & Business Media
Release Date : 2009-05-12
Computer Recognition Systems 3 written by Marek Kurzynski and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2009-05-12 with Technology & Engineering categories.
This book presents latest results in computer recognition systems, pattern recognition, machine learning, web and data mining. It includes coverage of image processing and computer vision; speech and word recognition; and medical applications.
Advances In Soft Computing And Machine Learning In Image Processing
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Author : Aboul Ella Hassanien
language : en
Publisher: Springer
Release Date : 2017-10-13
Advances In Soft Computing And Machine Learning In Image Processing written by Aboul Ella Hassanien and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017-10-13 with Technology & Engineering categories.
This book is a collection of the latest applications of methods from soft computing and machine learning in image processing. It explores different areas ranging from image segmentation to the object recognition using complex approaches, and includes the theory of the methodologies used to provide an overview of the application of these tools in image processing. The material has been compiled from a scientific perspective, and the book is primarily intended for undergraduate and postgraduate science, engineering, and computational mathematics students. It can also be used for courses on artificial intelligence, advanced image processing, and computational intelligence, and is a valuable resource for researchers in the evolutionary computation, artificial intelligence and image processing communities.
Computer Vision And Recognition Systems Using Machine And Deep Learning Approaches
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Author : Chiranji Lal Chowdhary
language : en
Publisher: Computing and Networks
Release Date : 2021-11
Computer Vision And Recognition Systems Using Machine And Deep Learning Approaches written by Chiranji Lal Chowdhary and has been published by Computing and Networks this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-11 with Computers categories.
Written by a team of International experts, this edited book covers state-of-the-art research in the fields of computer vision and recognition systems from fundamental concepts to methodologies and technologies and real-world applications. The book will be useful for industry and academic researchers, scientists and engineers.
Low Power Computer Vision
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Author : George K. Thiruvathukal
language : en
Publisher: CRC Press
Release Date : 2022-02-22
Low Power Computer Vision written by George K. Thiruvathukal and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-02-22 with Computers categories.
Energy efficiency is critical for running computer vision on battery-powered systems, such as mobile phones or UAVs (unmanned aerial vehicles, or drones). This book collects the methods that have won the annual IEEE Low-Power Computer Vision Challenges since 2015. The winners share their solutions and provide insight on how to improve the efficiency of machine learning systems.
Granular Video Computing With Rough Sets Deep Learning And In Iot
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Author : Debarati Bhunia Chakraborty
language : en
Publisher: World Scientific
Release Date : 2021-02-04
Granular Video Computing With Rough Sets Deep Learning And In Iot written by Debarati Bhunia Chakraborty and has been published by World Scientific this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-02-04 with Computers categories.
This volume links the concept of granular computing using deep learning and the Internet of Things to object tracking for video analysis. It describes how uncertainties, involved in the task of video processing, could be handled in rough set theoretic granular computing frameworks. Issues such as object tracking from videos in constrained situations, occlusion/overlapping handling, measuring of the reliability of tracking methods, object recognition and linguistic interpretation in video scenes, and event prediction from videos, are the addressed in this volume. The book also looks at ways to reduce data dependency in the context of unsupervised (without manual interaction/ labeled data/ prior information) training.This book may be used both as a textbook and reference book for graduate students and researchers in computer science, electrical engineering, system science, data science, and information technology, and is recommended for both students and practitioners working in computer vision, machine learning, video analytics, image analytics, artificial intelligence, system design, rough set theory, granular computing, and soft computing.
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.
Building Computer Vision Applications Using Artificial Neural Networks
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Author : Shamshad Ansari
language : en
Publisher: Apress
Release Date : 2020-07-17
Building Computer Vision Applications Using Artificial Neural Networks written by Shamshad Ansari and has been published by Apress this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-07-17 with Computers categories.
Apply computer vision and machine learning concepts in developing business and industrial applications using a practical, step-by-step approach. The book comprises four main sections starting with setting up your programming environment and configuring your computer with all the prerequisites to run the code examples. Section 1 covers the basics of image and video processing with code examples of how to manipulate and extract useful information from the images. You will mainly use OpenCV with Python to work with examples in this section. Section 2 describes machine learning and neural network concepts as applied to computer vision. You will learn different algorithms of the neural network, such as convolutional neural network (CNN), region-based convolutional neural network (R-CNN), and YOLO. In this section, you will also learn how to train, tune, and manage neural networks for computer vision. Section 3 provides step-by-step examples of developing business and industrial applications, such as facial recognition in video surveillance and surface defect detection in manufacturing. The final section is about training neural networks involving a large number of images on cloud infrastructure, such as Amazon AWS, Google Cloud Platform, and Microsoft Azure. It walks you through the process of training distributed neural networks for computer vision on GPU-based cloud infrastructure. By the time you finish reading Building Computer Vision Applications Using Artificial Neural Networks and working through the code examples, you will have developed some real-world use cases of computer vision with deep learning. What You Will Learn · Employ image processing, manipulation, and feature extraction techniques · Work with various deep learning algorithms for computer vision · Train, manage, and tune hyperparameters of CNNs and object detection models, such as R-CNN, SSD, and YOLO · Build neural network models using Keras and TensorFlow · Discover best practices when implementing computer vision applications in business and industry · Train distributed models on GPU-based cloud infrastructure Who This Book Is For Data scientists, analysts, and machine learning and software engineering professionals with Python programming knowledge.