Person Re-Identification

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Publisher : Springer Science & Business Media
ISBN 13 : 144716296X
Total Pages : 446 pages
Book Rating : 4.4/5 (471 download)

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Book Synopsis Person Re-Identification by : Shaogang Gong

Download or read book Person Re-Identification written by Shaogang Gong and published by Springer Science & Business Media. This book was released on 2014-01-03 with total page 446 pages. Available in PDF, EPUB and Kindle. Book excerpt: The first book of its kind dedicated to the challenge of person re-identification, this text provides an in-depth, multidisciplinary discussion of recent developments and state-of-the-art methods. Features: introduces examples of robust feature representations, reviews salient feature weighting and selection mechanisms and examines the benefits of semantic attributes; describes how to segregate meaningful body parts from background clutter; examines the use of 3D depth images and contextual constraints derived from the visual appearance of a group; reviews approaches to feature transfer function and distance metric learning and discusses potential solutions to issues of data scalability and identity inference; investigates the limitations of existing benchmark datasets, presents strategies for camera topology inference and describes techniques for improving post-rank search efficiency; explores the design rationale and implementation considerations of building a practical re-identification system.

Advances and Applications in Deep Learning

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Publisher : BoD – Books on Demand
ISBN 13 : 1839628782
Total Pages : 124 pages
Book Rating : 4.8/5 (396 download)

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Book Synopsis Advances and Applications in Deep Learning by :

Download or read book Advances and Applications in Deep Learning written by and published by BoD – Books on Demand. This book was released on 2020-12-09 with total page 124 pages. Available in PDF, EPUB and Kindle. Book excerpt: Artificial Intelligence (AI) has attracted the attention of researchers and users alike and is taking an increasingly crucial role in our modern society. From cars, smartphones, and airplanes to medical equipment, consumer applications, and industrial machines, the impact of AI is notoriously changing the world we live in. In this context, Deep Learning (DL) is one of the techniques that has taken the lead for cognitive processes, pattern recognition, object detection, and machine learning, all of which have played a crucial role in the growth of AI. As such, this book examines DL applications and future trends in the field. It is a useful resource for researchers and students alike.

Information Processing in Medical Imaging

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Publisher : Springer
ISBN 13 : 3319590502
Total Pages : 691 pages
Book Rating : 4.3/5 (195 download)

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Book Synopsis Information Processing in Medical Imaging by : Marc Niethammer

Download or read book Information Processing in Medical Imaging written by Marc Niethammer and published by Springer. This book was released on 2017-06-06 with total page 691 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the proceedings of the 25th International Conference on Information Processing in Medical Imaging, IPMI 2017, held at the Appalachian State University, Boon, NC, USA, in June 2017. The 53 full papers presented in this volume were carefully reviewed and selected from 147 submissions. They were organized in topical sections named: analysis on manifolds; shape analysis; disease diagnosis/progression; brain networks an connectivity; diffusion imaging; quantitative imaging; imaging genomics; image registration; segmentation; general image analysis.

Proceedings of the TEPEN International Workshop on Fault Diagnostic and Prognostic

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Publisher : Springer Nature
ISBN 13 : 3031734076
Total Pages : 634 pages
Book Rating : 4.0/5 (317 download)

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Book Synopsis Proceedings of the TEPEN International Workshop on Fault Diagnostic and Prognostic by : Zuolu Wang

Download or read book Proceedings of the TEPEN International Workshop on Fault Diagnostic and Prognostic written by Zuolu Wang and published by Springer Nature. This book was released on with total page 634 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Domain Adaptation in Computer Vision with Deep Learning

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Publisher : Springer Nature
ISBN 13 : 3030455297
Total Pages : 256 pages
Book Rating : 4.0/5 (34 download)

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Book Synopsis Domain Adaptation in Computer Vision with Deep Learning by : Hemanth Venkateswara

Download or read book Domain Adaptation in Computer Vision with Deep Learning written by Hemanth Venkateswara and published by Springer Nature. This book was released on 2020-08-18 with total page 256 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book provides a survey of deep learning approaches to domain adaptation in computer vision. It gives the reader an overview of the state-of-the-art research in deep learning based domain adaptation. This book also discusses the various approaches to deep learning based domain adaptation in recent years. It outlines the importance of domain adaptation for the advancement of computer vision, consolidates the research in the area and provides the reader with promising directions for future research in domain adaptation. Divided into four parts, the first part of this book begins with an introduction to domain adaptation, which outlines the problem statement, the role of domain adaptation and the motivation for research in this area. It includes a chapter outlining pre-deep learning era domain adaptation techniques. The second part of this book highlights feature alignment based approaches to domain adaptation. The third part of this book outlines image alignment procedures for domain adaptation. The final section of this book presents novel directions for research in domain adaptation. This book targets researchers working in artificial intelligence, machine learning, deep learning and computer vision. Industry professionals and entrepreneurs seeking to adopt deep learning into their applications will also be interested in this book.

Domain Adaptation for Visual Understanding

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Publisher : Springer Nature
ISBN 13 : 3030306712
Total Pages : 148 pages
Book Rating : 4.0/5 (33 download)

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Book Synopsis Domain Adaptation for Visual Understanding by : Richa Singh

Download or read book Domain Adaptation for Visual Understanding written by Richa Singh and published by Springer Nature. This book was released on 2020-01-08 with total page 148 pages. Available in PDF, EPUB and Kindle. Book excerpt: This unique volume reviews the latest advances in domain adaptation in the training of machine learning algorithms for visual understanding, offering valuable insights from an international selection of experts in the field. The text presents a diverse selection of novel techniques, covering applications of object recognition, face recognition, and action and event recognition. Topics and features: reviews the domain adaptation-based machine learning algorithms available for visual understanding, and provides a deep metric learning approach; introduces a novel unsupervised method for image-to-image translation, and a video segment retrieval model that utilizes ensemble learning; proposes a unique way to determine which dataset is most useful in the base training, in order to improve the transferability of deep neural networks; describes a quantitative method for estimating the discrepancy between the source and target data to enhance image classification performance; presents a technique for multi-modal fusion that enhances facial action recognition, and a framework for intuition learning in domain adaptation; examines an original interpolation-based approach to address the issue of tracking model degradation in correlation filter-based methods. This authoritative work will serve as an invaluable reference for researchers and practitioners interested in machine learning-based visual recognition and understanding.

Advanced Methods and Deep Learning in Computer Vision

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Publisher : Academic Press
ISBN 13 : 0128221496
Total Pages : 584 pages
Book Rating : 4.1/5 (282 download)

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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

Research Anthology on Improving Medical Imaging Techniques for Analysis and Intervention

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Publisher : IGI Global
ISBN 13 : 1668475456
Total Pages : 1671 pages
Book Rating : 4.6/5 (684 download)

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Book Synopsis Research Anthology on Improving Medical Imaging Techniques for Analysis and Intervention by : Management Association, Information Resources

Download or read book Research Anthology on Improving Medical Imaging Techniques for Analysis and Intervention written by Management Association, Information Resources and published by IGI Global. This book was released on 2022-09-09 with total page 1671 pages. Available in PDF, EPUB and Kindle. Book excerpt: Medical imaging provides medical professionals the unique ability to investigate and diagnose injuries and illnesses without being intrusive. With the surge of technological advancement in recent years, the practice of medical imaging has only been improved through these technologies and procedures. It is essential to examine these innovations in medical imaging to implement and improve the practice around the world. The Research Anthology on Improving Medical Imaging Techniques for Analysis and Intervention investigates and presents the recent innovations, procedures, and technologies implemented in medical imaging. Covering topics such as automatic detection, simulation in medical education, and neural networks, this major reference work is an excellent resource for radiologists, medical professionals, hospital administrators, medical educators and students, librarians, researchers, and academicians.

Deep Learning Applications for Cyber Security

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Publisher : Springer
ISBN 13 : 3030130576
Total Pages : 260 pages
Book Rating : 4.0/5 (31 download)

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Book Synopsis Deep Learning Applications for Cyber Security by : Mamoun Alazab

Download or read book Deep Learning Applications for Cyber Security written by Mamoun Alazab and published by Springer. This book was released on 2019-08-14 with total page 260 pages. Available in PDF, EPUB and Kindle. Book excerpt: Cybercrime remains a growing challenge in terms of security and privacy practices. Working together, deep learning and cyber security experts have recently made significant advances in the fields of intrusion detection, malicious code analysis and forensic identification. This book addresses questions of how deep learning methods can be used to advance cyber security objectives, including detection, modeling, monitoring and analysis of as well as defense against various threats to sensitive data and security systems. Filling an important gap between deep learning and cyber security communities, it discusses topics covering a wide range of modern and practical deep learning techniques, frameworks and development tools to enable readers to engage with the cutting-edge research across various aspects of cyber security. The book focuses on mature and proven techniques, and provides ample examples to help readers grasp the key points.

Domain Adaptation in Computer Vision Applications

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Publisher : Springer
ISBN 13 : 3319583476
Total Pages : 338 pages
Book Rating : 4.3/5 (195 download)

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Book Synopsis Domain Adaptation in Computer Vision Applications by : Gabriela Csurka

Download or read book Domain Adaptation in Computer Vision Applications written by Gabriela Csurka and published by Springer. This book was released on 2017-09-10 with total page 338 pages. Available in PDF, EPUB and Kindle. Book excerpt: This comprehensive text/reference presents a broad review of diverse domain adaptation (DA) methods for machine learning, with a focus on solutions for visual applications. The book collects together solutions and perspectives proposed by an international selection of pre-eminent experts in the field, addressing not only classical image categorization, but also other computer vision tasks such as detection, segmentation and visual attributes. Topics and features: surveys the complete field of visual DA, including shallow methods designed for homogeneous and heterogeneous data as well as deep architectures; presents a positioning of the dataset bias in the CNN-based feature arena; proposes detailed analyses of popular shallow methods that addresses landmark data selection, kernel embedding, feature alignment, joint feature transformation and classifier adaptation, or the case of limited access to the source data; discusses more recent deep DA methods, including discrepancy-based adaptation networks and adversarial discriminative DA models; addresses domain adaptation problems beyond image categorization, such as a Fisher encoding adaptation for vehicle re-identification, semantic segmentation and detection trained on synthetic images, and domain generalization for semantic part detection; describes a multi-source domain generalization technique for visual attributes and a unifying framework for multi-domain and multi-task learning. This authoritative volume will be of great interest to a broad audience ranging from researchers and practitioners, to students involved in computer vision, pattern recognition and machine learning.

Recent Advances in Logo Detection Using Machine Learning Paradigms

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Publisher : Springer Nature
ISBN 13 : 3031598113
Total Pages : 128 pages
Book Rating : 4.0/5 (315 download)

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Book Synopsis Recent Advances in Logo Detection Using Machine Learning Paradigms by : Yen-Wei Chen

Download or read book Recent Advances in Logo Detection Using Machine Learning Paradigms written by Yen-Wei Chen and published by Springer Nature. This book was released on with total page 128 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Proceedings of IncoME-VI and TEPEN 2021

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Publisher : Springer Nature
ISBN 13 : 3030990753
Total Pages : 1074 pages
Book Rating : 4.0/5 (39 download)

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Book Synopsis Proceedings of IncoME-VI and TEPEN 2021 by : Hao Zhang

Download or read book Proceedings of IncoME-VI and TEPEN 2021 written by Hao Zhang and published by Springer Nature. This book was released on 2022-09-17 with total page 1074 pages. Available in PDF, EPUB and Kindle. Book excerpt: This volume gathers the latest advances, innovations and applications in the field of condition monitoring, plant maintenance and reliability, as presented by leading international researchers and engineers at the 6th International Conference on Maintenance Engineering and the 2021 conference of the Efficiency and Performance Engineering Network (IncoME-VI TEPEN 2021), held in Tianjin, China on October 20-23, 2021. Topics include vibro-acoustics monitoring, condition-based maintenance, sensing and instrumentation, machine health monitoring, maintenance auditing and organization, non-destructive testing, reliability, asset management, condition monitoring, life-cycle cost optimisation, prognostics and health management, maintenance performance measurement, manufacturing process monitoring, and robot-based monitoring and diagnostics. The contributions, which were selected through a rigorous international peer-review process, share exciting ideas that will spur novel research directions and foster new multidisciplinary collaborations.

Deep Learning Theory and Applications

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Publisher : Springer Nature
ISBN 13 : 3031373200
Total Pages : 163 pages
Book Rating : 4.0/5 (313 download)

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Book Synopsis Deep Learning Theory and Applications by : Ana Fred

Download or read book Deep Learning Theory and Applications written by Ana Fred and published by Springer Nature. This book was released on 2023-07-06 with total page 163 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the refereed post-proceedings of the First International Conference and Second International Conference on Deep Learning Theory and Applications, DeLTA 2020 and DeLTA 2021, was held virtually due to the COVID-19 crisis on July 8-10, 2020 and July 7–9, 2021. The 7 full papers included in this book were carefully reviewed and selected from 58 submissions. They present recent research on machine learning and artificial intelligence in real-world applications such as computer vision, information retrieval and summarization from structuredand unstructured multimodal data sources, natural language understanding andtranslation, and many other application domains.

Meta Learning With Medical Imaging and Health Informatics Applications

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Publisher : Academic Press
ISBN 13 : 0323998526
Total Pages : 430 pages
Book Rating : 4.3/5 (239 download)

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Book Synopsis Meta Learning With Medical Imaging and Health Informatics Applications by : Hien Van Nguyen

Download or read book Meta Learning With Medical Imaging and Health Informatics Applications written by Hien Van Nguyen and published by Academic Press. This book was released on 2022-09-24 with total page 430 pages. Available in PDF, EPUB and Kindle. Book excerpt: Meta-Learning, or learning to learn, has become increasingly popular in recent years. Instead of building AI systems from scratch for each machine learning task, Meta-Learning constructs computational mechanisms to systematically and efficiently adapt to new tasks. The meta-learning paradigm has great potential to address deep neural networks' fundamental challenges such as intensive data requirement, computationally expensive training, and limited capacity for transfer among tasks.This book provides a concise summary of Meta-Learning theories and their diverse applications in medical imaging and health informatics. It covers the unifying theory of meta-learning and its popular variants such as model-agnostic learning, memory augmentation, prototypical networks, and learning to optimize. The book brings together thought leaders from both machine learning and health informatics fields to discuss the current state of Meta-Learning, its relevance to medical imaging and health informatics, and future directions. - First book on applying Meta Learning to medical imaging - Pioneers in the field as contributing authors to explain the theory and its development - Has GitHub repository consisting of various code examples and documentation to help the audience to set up Meta-Learning algorithms for their applications quickly

Deep Learning for Marine Science

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Publisher : Frontiers Media SA
ISBN 13 : 2832549055
Total Pages : 555 pages
Book Rating : 4.8/5 (325 download)

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Book Synopsis Deep Learning for Marine Science by : Haiyong Zheng

Download or read book Deep Learning for Marine Science written by Haiyong Zheng and published by Frontiers Media SA. This book was released on 2024-05-15 with total page 555 pages. Available in PDF, EPUB and Kindle. Book excerpt: Deep learning (DL), mainly composed of deep and complex neural networks such as recurrent network and convolutional network, is an emerging research branch in the field of artificial intelligence and machine learning. DL revolution has a far-reaching impact on all scientific disciplines and every corner of our lives. With continuing technological advances, marine science is entering into the big data era with the exponential growth of information. DL is an effective means of harnessing the power of big data. Combined with unprecedented data from cameras, acoustic recorders, satellite remote sensing, and large model outputs, DL enables scientists to solve complex problems in biology, ecosystems, climate, energy, as well as physical and chemical interactions. Although DL has made great strides, it is still only beginning to emerge in many fields of marine science, especially towards representative applications and best practices for the automatic analysis of marine organisms and marine environments. DL in nowadays' marine science mainly leverages cutting-edge techniques of deep neural networks and massive data which collected by in-situ optical or acoustic imaging sensors for underwater applications, such as plankton classification and coral reef detection. This research topic aims to expand the applications of marine science to cover all aspects of detection, classification, segmentation, localization, and density estimation of marine objects, organisms, and phenomena.

Robust Representation for Data Analytics

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Publisher : Springer
ISBN 13 : 3319601768
Total Pages : 229 pages
Book Rating : 4.3/5 (196 download)

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Book Synopsis Robust Representation for Data Analytics by : Sheng Li

Download or read book Robust Representation for Data Analytics written by Sheng Li and published by Springer. This book was released on 2017-08-09 with total page 229 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book introduces the concepts and models of robust representation learning, and provides a set of solutions to deal with real-world data analytics tasks, such as clustering, classification, time series modeling, outlier detection, collaborative filtering, community detection, etc. Three types of robust feature representations are developed, which extend the understanding of graph, subspace, and dictionary. Leveraging the theory of low-rank and sparse modeling, the authors develop robust feature representations under various learning paradigms, including unsupervised learning, supervised learning, semi-supervised learning, multi-view learning, transfer learning, and deep learning. Robust Representations for Data Analytics covers a wide range of applications in the research fields of big data, human-centered computing, pattern recognition, digital marketing, web mining, and computer vision.

Wireless Algorithms, Systems, and Applications

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Publisher : Springer Nature
ISBN 13 : 3031192087
Total Pages : 687 pages
Book Rating : 4.0/5 (311 download)

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Book Synopsis Wireless Algorithms, Systems, and Applications by : Lei Wang

Download or read book Wireless Algorithms, Systems, and Applications written by Lei Wang and published by Springer Nature. This book was released on 2022-11-17 with total page 687 pages. Available in PDF, EPUB and Kindle. Book excerpt: The three-volume set constitutes the proceedings of the 17th International Conference on Wireless Algorithms, Systems, and Applications, WASA 2022, which was held during November 24th-26th, 2022. The conference took place in Dalian, China.The 95 full and 62 short papers presented in these proceedings were carefully reviewed and selected from 265 submissions. The contributions in cyber-physical systems including intelligent transportation systems and smart healthcare systems; security and privacy; topology control and coverage; energy-efficient algorithms, systems and protocol design