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检索条件"丛书名=Advances in Computer Vision and Pattern Recognition"

共 114 条记录，以下是11-20 订阅

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Contactless 3D Fingerprint Identification 1st ed. 2018

引用

丛书名： advances in computer vision and pattern recognition

2018年

作者： Ajay Kumar

ISBN: (数字)9783319676814

ISBN: (纸本)9783319676807

This important text/reference presents the first dedicated review of techniques for contactless 3D fingerprint identification, including novel and previously unpublished research. The text provides a systematic introduction to 3D fingerprint identification, covering the latest advancements in contactless 2D and 3D sensing technologies, and detailed discussions on each key aspect in the development of an effective 3D fingerprint identification system. Topics and features: introduces the key concepts and trends in the acquisition and identification of fingerprint images, and a range of 3D fingerprint imaging techniques; proposes a low-cost method for online 3D fingerprint image acquisition, and an efficient 3D fingerprint imaging approach using coloured photometric stereo; describes pre-processing operations on point cloud 3D fingerprint data, and explains the specialized operations for reconstructing 3D fingerprints from live finger scans; examines the representation of minutiae in 3D space, providing details on recovering these features from point cloud data, and on matching such 3D minutiae templates; reviews various 3D fingerprint matching methods, including binary surface code-based approaches and a tetrahedron-based matching approach; discusses the uniqueness of 3D fingerprints, evaluating the benefits of employing 3D fingerprint identification over conventional 2D fingerprint techniques. This unique work is a must-read for all researchers seeking to make further advances in this area, towards the exciting opportunities afforded by contactless 3D fingerprint identification for improving the hygiene, user convenience, and matching accuracy of fingerprint biometric technologies.

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Handbook of biometrics for forensic science /

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2017年

作者： Massimo Tistarelli Christophe Champod editors.

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Deep Learning for Biometrics 1st ed. 2017

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丛书名： advances in computer vision and pattern recognition

2017年

作者： Bir Bhanu Ajay Kumar

ISBN: (数字)9783319616575

ISBN: (纸本)9783319616568

This timely text/reference presents a broad overview of advanced deep learning architectures for learning effective feature representation for perceptual and biometrics-related tasks. The text offers a showcase of cutting-edge research on the use of convolutional neural networks (CNN) in face, iris, fingerprint, and vascular biometric systems, in addition to surveillance systems that use soft biometrics. Issues of biometrics security are also examined. Topics and features: addresses the application of deep learning to enhance the performance of biometrics identification across a wide range of different biometrics modalities; revisits deep learning for face biometrics, offering insights from neuroimaging, and provides comparison with popular CNN-based architectures for face recognition; examines deep learning for state-of-the-art latent fingerprint and finger-vein recognition, as well as iris recognition; discusses deep learning for soft biometrics, including approaches for gesture-based identification, gender classification, and tattoo recognition; investigates deep learning for biometrics security, covering biometrics template protection methods, and liveness detection to protect against fake biometrics samples; presents contributions from a global selection of pre-eminent experts in the field representing academia, industry and government laboratories. Providing both an accessible introduction to the practical applications of deep learning in biometrics, and a comprehensive coverage of the entire spectrum of biometric modalities, this authoritative volume will be of great interest to all researchers, practitioners and students involved in related areas of computer vision, pattern recognition and machine learning.

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Domain Adaptation in computer vision Applications 1st ed. 2017

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丛书名： advances in computer vision and pattern recognition

2017年

作者： Gabriela Csurka

ISBN: (数字)9783319583471

ISBN: (纸本)9783319583464

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.

关键词： computer science. Artificial intelligence. Image processing. Application software.

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Deep Learning and Convolutional Neural Networks for Medical Image Computing 1st ed. 2017

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丛书名： advances in computer vision and pattern recognition

2017年

作者： Le Lu Yefeng Zheng Gustavo Carneiro Lin Yang

ISBN: (数字)9783319429991

ISBN: (纸本)9783319429984

This book presents a detailed review of the state of the art in deep learning approaches for semantic object detection and segmentation in medical image computing, and large-scale radiology database mining. A particular focus is placed on the application of convolutional neural networks, with the theory supported by practical examples. Features: highlights how the use of deep neural networks can address new questions and protocols, as well as improve upon existing challenges in medical image computing; discusses the insightful research experience of Dr. Ronald M. Summers; presents a comprehensive review of the latest research and literature; describes a range of different methods that make use of deep learning for object or landmark detection tasks in 2D and 3D medical imaging; examines a varied selection of techniques for semantic segmentation using deep learning principles in medical imaging; introduces a novel approach to interleaved text and image deep mining on a large-scale radiology image database.

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Visual Attributes 1st ed. 2017

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丛书名： advances in computer vision and pattern recognition

2017年

作者： Rogerio Schmidt Feris Christoph Lampert Devi Parikh

ISBN: (数字)9783319500775

ISBN: (纸本)9783319500751

This unique text/reference provides a detailed overview of the latest advances in machine learning and computer vision related to visual attributes, highlighting how this emerging field intersects with other disciplines, such as computational linguistics and human-machine interaction. Topics and features: presents attribute-based methods for zero-shot classification, learning using privileged information, and methods for multi-task attribute learning; describes the concept of relative attributes, and examines the effectiveness of modeling relative attributes in image search applications; reviews state-of-the-art methods for estimation of human attributes, and describes their use in a range of different applications; discusses attempts to build a vocabulary of visual attributes; explores the connections between visual attributes and natural language; provides contributions from an international selection of world-renowned scientists, covering both theoretical aspects and practical applications.

关键词： computer vision. Machine learning. Attribute (Philosophy) Categories (Philosophy)

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Guide to Medical Image Analysis 2nd ed. 2017

引用

丛书名： advances in computer vision and pattern recognition

2017年

作者： Klaus D. Toennies

ISBN: (数字)9781447173205

ISBN: (纸本)9781447173182

This comprehensive guide provides a uniquely practical, application-focused introduction to medical image analysis. This fully updated new edition has been enhanced with material on the latest developments in the field, whilst retaining the original focus on segmentation, classification and registration. Topics and features: presents learning objectives, exercises and concluding remarks in each chapter; describes a range of common imaging techniques, reconstruction techniques and image artifacts, and discusses the archival and transfer of images; reviews an expanded selection of techniques for image enhancement, feature detection, feature generation, segmentation, registration, and validation; examines analysis methods in view of image-based guidance in the operating room (NEW); discusses the use of deep convolutional networks for segmentation and labeling tasks (NEW); includes appendices on Markov random field optimization, variational calculus and principal component analysis.

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Handbook of Iris recognition 2nd ed. 2016

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丛书名： advances in computer vision and pattern recognition

2016年

作者： Kevin W. Bowyer Mark J. Burge

ISBN: (数字)9781447167846

ISBN: (纸本)9781447167822

The definitive work on iris recognition technology, this comprehensive handbook presents a broad overview of the state of the art in this exciting and rapidly evolving field. Revised and updated from the highly-successful original, this second edition has also been considerably expanded in scope and content, featuring four completely new chapters. Features: provides authoritative insights from an international selection of preeminent researchers from government, industry, and academia; reviews issues covering the full spectrum of the iris recognition process, from acquisition to encoding; presents surveys of topical areas, and discusses the frontiers of iris research, including cross-wavelength matching, iris template aging, and anti-spoofing; describes open source software for the iris recognition pipeline and datasets of iris images; includes new content on liveness detection, correcting off-angle iris images, subjects with eye conditions, and implementing software systems for iris recognition.

关键词： Biometric identification pattern recognition systems Optical pattern recognition

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Knowledge Transfer between computer vision and Text Mining 1st ed. 2016

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丛书名： advances in computer vision and pattern recognition

2016年

作者： Radu Tudor Ionescu Marius Popescu

ISBN: (数字)9783319303673

ISBN: (纸本)9783319303659

This ground-breaking text/reference diverges from the traditional view that computer vision (for image analysis) and string processing (for text mining) are separate and unrelated fields of study, propounding that images and text can be treated in a similar manner for the purposes of information retrieval, extraction and classification. Highlighting the benefits of knowledge transfer between the two disciplines, the text presents a range of novel similarity-based learning (SBL) techniques founded on this approach. Topics and features: describes a variety of SBL approaches, including nearest neighbor models, local learning, kernel methods, and clustering algorithms; presents a nearest neighbor model based on a novel dissimilarity for images; discusses a novel kernel for (visual) word histograms, as well as several kernels based on a pyramid representation; introduces an approach based on string kernels for native language identification; contains links for downloading relevant open source code.

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Context-Enhanced Information Fusion 1st ed. 2016

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丛书名： advances in computer vision and pattern recognition

2016年

作者： Lauro Snidaro Jesús García James Llinas Erik Blasch

ISBN: (数字)9783319289717

ISBN: (纸本)9783319289694

This text reviews the fundamental theory and latest methods for including contextual information in fusion process design and implementation. Chapters are contributed by the foremost international experts, spanning numerous developments and applications. The book highlights high- and low-level information fusion problems, performance evaluation under highly demanding conditions, and design principles. A particular focus is placed on approaches that integrate research from different communities, emphasizing the benefit of combining different techniques to overcome the limitations of a single perspective. Features: introduces the terminology and core elements in information fusion and context; presents key themes for context-enhanced information fusion; discusses design issues in developing context-aware fusion systems; provides mathematical grounds for modeling the contextual influences in representative fusion problems; describes the fusion of hard and soft data; reviews a diverse range of applications.

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