Read Books Online and Download eBooks, EPub, PDF, Mobi, Kindle, Text Full Free.
Advances In Machine Vision
Download Advances In Machine Vision full books in PDF, epub, and Kindle. Read online Advances In Machine Vision ebook anywhere anytime directly on your device. Fast Download speed and no annoying ads. We cannot guarantee that every ebooks is available!
Book Synopsis Advances in Machine Vision by : Jorge L.C. Sanz
Download or read book Advances in Machine Vision written by Jorge L.C. Sanz and published by Springer Science & Business Media. This book was released on 2012-12-06 with total page 432 pages. Available in PDF, EPUB and Kindle. Book excerpt: Machine Vision technology is becoming an indispensible part of the manufacturing industry. Biomedical and scientific applications of machine vision and imaging are becoming more and more sophisticated, and new applications continue to emerge. This book gives an overview of ongoing research in machine vision and presents the key issues of scientific and practical interest. A selected board of experts from the US, Japan and Europe provides an insight into some of the latest work done on machine vision systems and appliccations.
Book Synopsis Recent Advances in Computer Vision by : Mahmoud Hassaballah
Download or read book Recent Advances in Computer Vision written by Mahmoud Hassaballah and published by Springer. This book was released on 2018-12-14 with total page 425 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book presents a collection of high-quality research by leading experts in computer vision and its applications. Each of the 16 chapters can be read independently and discusses the principles of a specific topic, reviews up-to-date techniques, presents outcomes, and highlights the challenges and future directions. As such the book explores the latest trends in fashion creative processes, facial features detection, visual odometry, transfer learning, face recognition, feature description, plankton and scene classification, video face alignment, video searching, and object segmentation. It is intended for postgraduate students, researchers, scholars and developers who are interested in computer vision and connected research disciplines, and is also suitable for senior undergraduate students who are taking advanced courses in related topics. However, it is also provides a valuable reference resource for practitioners from industry who want to keep abreast of recent developments in this dynamic, exciting and profitable research field.
Book Synopsis Advances in Computer Vision by : Kohei Arai
Download or read book Advances in Computer Vision written by Kohei Arai and published by Springer. This book was released on 2019-04-23 with total page 767 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book presents a remarkable collection of chapters covering a wide range of topics in the areas of Computer Vision, both from theoretical and application perspectives. It gathers the proceedings of the Computer Vision Conference (CVC 2019), held in Las Vegas, USA from May 2 to 3, 2019. The conference attracted a total of 371 submissions from pioneering researchers, scientists, industrial engineers, and students all around the world. These submissions underwent a double-blind peer review process, after which 118 (including 7 poster papers) were selected for inclusion in these proceedings. The book’s goal is to reflect the intellectual breadth and depth of current research on computer vision, from classical to intelligent scope. Accordingly, its respective chapters address state-of-the-art intelligent methods and techniques for solving real-world problems, while also outlining future research directions. Topic areas covered include Machine Vision and Learning, Data Science, Image Processing, Deep Learning, and Computer Vision Applications.
Book Synopsis Advanced Machine Vision Paradigms for Medical Image Analysis by : Tapan K. Gandhi
Download or read book Advanced Machine Vision Paradigms for Medical Image Analysis written by Tapan K. Gandhi and published by Academic Press. This book was released on 2020-08-11 with total page 308 pages. Available in PDF, EPUB and Kindle. Book excerpt: Computer vision and machine intelligence paradigms are prominent in the domain of medical image applications, including computer assisted diagnosis, image guided radiation therapy, landmark detection, imaging genomics, and brain connectomics. Medical image analysis and understanding are daunting tasks owing to the massive influx of multi-modal medical image data generated during routine clinal practice. Advanced computer vision and machine intelligence approaches have been employed in recent years in the field of image processing and computer vision. However, due to the unstructured nature of medical imaging data and the volume of data produced during routine clinical processes, the applicability of these meta-heuristic algorithms remains to be investigated. Advanced Machine Vision Paradigms for Medical Image Analysis presents an overview of how medical imaging data can be analyzed to provide better diagnosis and treatment of disease. Computer vision techniques can explore texture, shape, contour and prior knowledge along with contextual information, from image sequence and 3D/4D information which helps with better human understanding. Many powerful tools have been developed through image segmentation, machine learning, pattern classification, tracking, and reconstruction to surface much needed quantitative information not easily available through the analysis of trained human specialists. The aim of the book is for medical imaging professionals to acquire and interpret the data, and for computer vision professionals to learn how to provide enhanced medical information by using computer vision techniques. The ultimate objective is to benefit patients without adding to already high healthcare costs. Explores major emerging trends in technology which are supporting the current advancement of medical image analysis with the help of computational intelligence Highlights the advancement of conventional approaches in the field of medical image processing Investigates novel techniques and reviews the state-of-the-art in the areas of machine learning, computer vision, soft computing techniques, as well as their applications in medical image analysis
Author :Giovanni Maria Farinella Publisher :Springer Science & Business Media ISBN 13 :1447155203 Total Pages :433 pages Book Rating :4.4/5 (471 download)
Book Synopsis Advanced Topics in Computer Vision by : Giovanni Maria Farinella
Download or read book Advanced Topics in Computer Vision written by Giovanni Maria Farinella and published by Springer Science & Business Media. This book was released on 2013-09-24 with total page 433 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book presents a broad selection of cutting-edge research, covering both theoretical and practical aspects of reconstruction, registration, and recognition. The text provides an overview of challenging areas and descriptions of novel algorithms. Features: investigates visual features, trajectory features, and stereo matching; reviews the main challenges of semi-supervised object recognition, and a novel method for human action categorization; presents a framework for the visual localization of MAVs, and for the use of moment constraints in convex shape optimization; examines solutions to the co-recognition problem, and distance-based classifiers for large-scale image classification; describes how the four-color theorem can be used for solving MRF problems; introduces a Bayesian generative model for understanding indoor environments, and a boosting approach for generalizing the k-NN rule; discusses the issue of scene-specific object detection, and an approach for making temporal super resolution video.
Book Synopsis Advanced Methods and Deep Learning in Computer Vision by : E. R. Davies
Download or read book Advanced Methods and Deep Learning in Computer Vision written by E. R. Davies and published by Academic Press. This book was released on 2021-11-09 with total page 584 pages. Available in PDF, EPUB and Kindle. Book excerpt: Advanced Methods and Deep Learning in Computer Vision presents advanced computer vision methods, emphasizing machine and deep learning techniques that have emerged during the past 5–10 years. The book provides clear explanations of principles and algorithms supported with applications. Topics covered include machine learning, deep learning networks, generative adversarial networks, deep reinforcement learning, self-supervised learning, extraction of robust features, object detection, semantic segmentation, linguistic descriptions of images, visual search, visual tracking, 3D shape retrieval, image inpainting, novelty and anomaly detection. This book provides easy learning for researchers and practitioners of advanced computer vision methods, but it is also suitable as a textbook for a second course on computer vision and deep learning for advanced undergraduates and graduate students. Provides an important reference on deep learning and advanced computer methods that was created by leaders in the field Illustrates principles with modern, real-world applications Suitable for self-learning or as a text for graduate courses
Book Synopsis Advances in Computer Vision by : Kohei Arai
Download or read book Advances in Computer Vision written by Kohei Arai and published by Springer. This book was released on 2019-04-23 with total page 821 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book presents a remarkable collection of chapters covering a wide range of topics in the areas of Computer Vision, both from theoretical and application perspectives. It gathers the proceedings of the Computer Vision Conference (CVC 2019), held in Las Vegas, USA from May 2 to 3, 2019. The conference attracted a total of 371 submissions from pioneering researchers, scientists, industrial engineers, and students all around the world. These submissions underwent a double-blind peer review process, after which 120 (including 7 poster papers) were selected for inclusion in these proceedings. The book’s goal is to reflect the intellectual breadth and depth of current research on computer vision, from classical to intelligent scope. Accordingly, its respective chapters address state-of-the-art intelligent methods and techniques for solving real-world problems, while also outlining future research directions. Topic areas covered include Machine Vision and Learning, Data Science, Image Processing, Deep Learning, and Computer Vision Applications.
Book Synopsis Advancements in Computer Vision and Image Processing by : Garcia-Rodriguez, Jose
Download or read book Advancements in Computer Vision and Image Processing written by Garcia-Rodriguez, Jose and published by IGI Global. This book was released on 2018-04-06 with total page 322 pages. Available in PDF, EPUB and Kindle. Book excerpt: Interest in computer vision and image processing has grown in recent years with the advancement of everyday technologies such as smartphones, computer games, and social robotics. These advancements have allowed for advanced algorithms that have improved the processing capabilities of these technologies. Advancements in Computer Vision and Image Processing is a critical scholarly resource that explores the impact of new technologies on computer vision and image processing methods in everyday life. Featuring coverage on a wide range of topics including 3D visual localization, cellular automata-based structures, and eye and face recognition, this book is geared toward academicians, technology professionals, engineers, students, and researchers seeking current research on the development of sophisticated algorithms to process images and videos in real time.
Book Synopsis Challenges and Applications for Implementing Machine Learning in Computer Vision by : Kashyap, Ramgopal
Download or read book Challenges and Applications for Implementing Machine Learning in Computer Vision written by Kashyap, Ramgopal and published by IGI Global. This book was released on 2019-10-04 with total page 293 pages. Available in PDF, EPUB and Kindle. Book excerpt: Machine learning allows for non-conventional and productive answers for issues within various fields, including problems related to visually perceptive computers. Applying these strategies and algorithms to the area of computer vision allows for higher achievement in tasks such as spatial recognition, big data collection, and image processing. There is a need for research that seeks to understand the development and efficiency of current methods that enable machines to see. Challenges and Applications for Implementing Machine Learning in Computer Vision is a collection of innovative research that combines theory and practice on adopting the latest deep learning advancements for machines capable of visual processing. Highlighting a wide range of topics such as video segmentation, object recognition, and 3D modelling, this publication is ideally designed for computer scientists, medical professionals, computer engineers, information technology practitioners, industry experts, scholars, researchers, and students seeking current research on the utilization of evolving computer vision techniques.
Book Synopsis Advancements in Computer Vision Applications in Intelligent Systems and Multimedia Technologies by : Muhammad Sarfraz
Download or read book Advancements in Computer Vision Applications in Intelligent Systems and Multimedia Technologies written by Muhammad Sarfraz and published by Engineering Science Reference. This book was released on 2020 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: "This book discusses innovative developments in computational imaging for solving real-life issues and problems and addresses their execution in various disciplines"--
Book Synopsis Computer Vision: Advanced Techniques and Applications by : Steve Holden
Download or read book Computer Vision: Advanced Techniques and Applications written by Steve Holden and published by . This book was released on 2019-06-05 with total page 215 pages. Available in PDF, EPUB and Kindle. Book excerpt: Computer vision is the field of science that is concerned with the development of computers to achieve high-level understanding using digital images or videos. It includes the processes of acquiring, processing and understanding of digital images. It also involves the extraction of data from the real world for the purpose of producing numerical or symbolic information. Some of the areas of interest in computer vision include scene reconstruction, object recognition, 3D pose interpretation, motion estimation, image restoration, etc. The applications of computer vision are in the development of artificial intelligence, surveillance, medical imaging, topographical modeling, navigation, among many others. This book brings forth some of the most innovative concepts and elucidates the unexplored aspects of this discipline. From theories to research to practical applications, studies related to all contemporary topics of relevance to this field have also been included. This book attempts to assist those with a goal of delving into the field of computer vision.
Book Synopsis Advances in Soft Computing and Machine Learning in Image Processing by : Aboul Ella Hassanien
Download or read book Advances in Soft Computing and Machine Learning in Image Processing written by Aboul Ella Hassanien and published by Springer. This book was released on 2017-10-13 with total page 718 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
Book Synopsis Advances in Financial Machine Learning by : Marcos Lopez de Prado
Download or read book Advances in Financial Machine Learning written by Marcos Lopez de Prado and published by John Wiley & Sons. This book was released on 2018-01-23 with total page 400 pages. Available in PDF, EPUB and Kindle. Book excerpt: Machine learning (ML) is changing virtually every aspect of our lives. Today ML algorithms accomplish tasks that until recently only expert humans could perform. As it relates to finance, this is the most exciting time to adopt a disruptive technology that will transform how everyone invests for generations. Readers will learn how to structure Big data in a way that is amenable to ML algorithms; how to conduct research with ML algorithms on that data; how to use supercomputing methods; how to backtest your discoveries while avoiding false positives. The book addresses real-life problems faced by practitioners on a daily basis, and explains scientifically sound solutions using math, supported by code and examples. Readers become active users who can test the proposed solutions in their particular setting. Written by a recognized expert and portfolio manager, this book will equip investment professionals with the groundbreaking tools needed to succeed in modern finance.
Book Synopsis Research Developments in Computer Vision and Image Processing: Methodologies and Applications by : Srivastava, Rajeev
Download or read book Research Developments in Computer Vision and Image Processing: Methodologies and Applications written by Srivastava, Rajeev and published by IGI Global. This book was released on 2013-09-30 with total page 451 pages. Available in PDF, EPUB and Kindle. Book excerpt: Similar to the way in which computer vision and computer graphics act as the dual fields that connect image processing in modern computer science, the field of image processing can be considered a crucial middle road between the vision and graphics fields. Research Developments in Computer Vision and Image Processing: Methodologies and Applications brings together various research methodologies and trends in emerging areas of application of computer vision and image processing. This book is useful for students, researchers, scientists, and engineers interested in the research developments of this rapidly growing field.
Book Synopsis Advances in Machine Vision by : Colin Archibald
Download or read book Advances in Machine Vision written by Colin Archibald and published by World Scientific. This book was released on 1992 with total page 382 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book describes recent strategies and applications for extracting useful information from sensor data. For example, the methods presented by Roth and Levine are becoming widely accepted as the ?best? way to segment range images, and the neural network methods for Alpha-numeric character recognition, presented by K Yamada, are believed to be the best yet presented. An applied system to analyze the images of dental imprints presented by J Ct, et al. is one of several examples of image processing systems that have already been proven to be practical, and can serve as a model for the image processing system designer. Important aspects of the automation of processes are presented in a practical way which can provide immediate new capabilities in fields as diverse as biomedical image processing, document processing, industrial automation, understanding human perception, and the defence industries. The book is organized into sections describing Model Driven Feature Extraction, Data Driven Feature Extraction, Neural Networks, Model Building, and Applications.
Book Synopsis Modern Computer Vision with PyTorch by : V Kishore Ayyadevara
Download or read book Modern Computer Vision with PyTorch written by V Kishore Ayyadevara and published by Packt Publishing Ltd. This book was released on 2020-11-27 with total page 805 pages. Available in PDF, EPUB and Kindle. Book excerpt: Get to grips with deep learning techniques for building image processing applications using PyTorch with the help of code notebooks and test questions Key FeaturesImplement solutions to 50 real-world computer vision applications using PyTorchUnderstand the theory and working mechanisms of neural network architectures and their implementationDiscover best practices using a custom library created especially for this bookBook Description Deep learning is the driving force behind many recent advances in various computer vision (CV) applications. This book takes a hands-on approach to help you to solve over 50 CV problems using PyTorch1.x on real-world datasets. You’ll start by building a neural network (NN) from scratch using NumPy and PyTorch and discover best practices for tweaking its hyperparameters. You’ll then perform image classification using convolutional neural networks and transfer learning and understand how they work. As you progress, you’ll implement multiple use cases of 2D and 3D multi-object detection, segmentation, human-pose-estimation by learning about the R-CNN family, SSD, YOLO, U-Net architectures, and the Detectron2 platform. The book will also guide you in performing facial expression swapping, generating new faces, and manipulating facial expressions as you explore autoencoders and modern generative adversarial networks. You’ll learn how to combine CV with NLP techniques, such as LSTM and transformer, and RL techniques, such as Deep Q-learning, to implement OCR, image captioning, object detection, and a self-driving car agent. Finally, you'll move your NN model to production on the AWS Cloud. By the end of this book, you’ll be able to leverage modern NN architectures to solve over 50 real-world CV problems confidently. What you will learnTrain a NN from scratch with NumPy and PyTorchImplement 2D and 3D multi-object detection and segmentationGenerate digits and DeepFakes with autoencoders and advanced GANsManipulate images using CycleGAN, Pix2PixGAN, StyleGAN2, and SRGANCombine CV with NLP to perform OCR, image captioning, and object detectionCombine CV with reinforcement learning to build agents that play pong and self-drive a carDeploy a deep learning model on the AWS server using FastAPI and DockerImplement over 35 NN architectures and common OpenCV utilitiesWho this book is for This book is for beginners to PyTorch and intermediate-level machine learning practitioners who are looking to get well-versed with computer vision techniques using deep learning and PyTorch. If you are just getting started with neural networks, you’ll find the use cases accompanied by notebooks in GitHub present in this book useful. Basic knowledge of the Python programming language and machine learning is all you need to get started with this book.
Book Synopsis Computer Vision Technology for Food Quality Evaluation by : Da-Wen Sun
Download or read book Computer Vision Technology for Food Quality Evaluation written by Da-Wen Sun and published by Elsevier. This book was released on 2011-04-28 with total page 600 pages. Available in PDF, EPUB and Kindle. Book excerpt: The first book in this rapidly expanding area, Computer Vision Technology for Food Quality Evaluation thoroughly discusses the latest advances in image processing and analysis. Computer vision has attracted much research and development attention in recent years and, as a result, significant scientific and technological advances have been made in quality inspection, classification and evaluation of a wide range of food and agricultural products. This unique work provides engineers and technologists working in research, development, and operations in the food industry with critical, comprehensive and readily accessible information on the art and science of computer vision technology. Undergraduate and postgraduate students and researchers in universities and research institutions will also find this an essential reference source. · Discusses novel technology for recognizing objects and extracting quantitative information from digital images in order to provide objective, rapid, non-contact and non-destructive quality evaluation. · International authors with both academic and professional credentials address in detail one aspect of the relevant technology per chapter making this ideal for textbook use · Divided into three parts, it begins with an outline of the fundamentals of the technology, followed by full coverage of the application in the most researched areas of meats and other foods, fruits, vegetables and grains.
