Read Books Online and Download eBooks, EPub, PDF, Mobi, Kindle, Text Full Free.
Robust Recognition Via Information Theoretic Learning
Download Robust Recognition Via Information Theoretic Learning full books in PDF, epub, and Kindle. Read online Robust Recognition Via Information Theoretic Learning ebook anywhere anytime directly on your device. Fast Download speed and no annoying ads. We cannot guarantee that every ebooks is available!
Book Synopsis Robust Recognition via Information Theoretic Learning by : Ran He
Download or read book Robust Recognition via Information Theoretic Learning written by Ran He and published by Springer. This book was released on 2014-08-28 with total page 120 pages. Available in PDF, EPUB and Kindle. Book excerpt: This Springer Brief represents a comprehensive review of information theoretic methods for robust recognition. A variety of information theoretic methods have been proffered in the past decade, in a large variety of computer vision applications; this work brings them together, attempts to impart the theory, optimization and usage of information entropy. The authors resort to a new information theoretic concept, correntropy, as a robust measure and apply it to solve robust face recognition and object recognition problems. For computational efficiency, the brief introduces the additive and multiplicative forms of half-quadratic optimization to efficiently minimize entropy problems and a two-stage sparse presentation framework for large scale recognition problems. It also describes the strengths and deficiencies of different robust measures in solving robust recognition problems.
Book Synopsis Robust Recognition Via Information Theoretic Learning by : Ran He
Download or read book Robust Recognition Via Information Theoretic Learning written by Ran He and published by . This book was released on 2014-09-30 with total page 124 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Heterogeneous Facial Analysis and Synthesis by : Yi Li
Download or read book Heterogeneous Facial Analysis and Synthesis written by Yi Li and published by Springer Nature. This book was released on 2020-06-24 with total page 104 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book presents a comprehensive review of heterogeneous face analysis and synthesis, ranging from the theoretical and technical foundations to various hot and emerging applications, such as cosmetic transfer, cross-spectral hallucination and face rotation. Deep generative models have been at the forefront of research on artificial intelligence in recent years and have enhanced many heterogeneous face analysis tasks. Not only has there been a constantly growing flow of related research papers, but there have also been substantial advances in real-world applications. Bringing these together, this book describes both the fundamentals and applications of heterogeneous face analysis and synthesis. Moreover, it discusses the strengths and weaknesses of related methods and outlines future trends. Offering a rich blend of theory and practice, the book represents a valuable resource for students, researchers and practitioners who need to construct face analysis systems with deep generative networks.
Book Synopsis Intelligence Science and Big Data Engineering. Big Data and Machine Learning by : Zhen Cui
Download or read book Intelligence Science and Big Data Engineering. Big Data and Machine Learning written by Zhen Cui and published by Springer Nature. This book was released on 2019-11-28 with total page 473 pages. Available in PDF, EPUB and Kindle. Book excerpt: The two volumes LNCS 11935 and 11936 constitute the proceedings of the 9th International Conference on Intelligence Science and Big Data Engineering, IScIDE 2019, held in Nanjing, China, in October 2019. The 84 full papers presented were carefully reviewed and selected from 252 submissions.The papers are organized in two parts: visual data engineering; and big data and machine learning. They cover a large range of topics including information theoretic and Bayesian approaches, probabilistic graphical models, big data analysis, neural networks and neuro-informatics, bioinformatics, computational biology and brain-computer interfaces, as well as advances in fundamental pattern recognition techniques relevant to image processing, computer vision and machine learning.
Book Synopsis Data Science by : Carlos Alberto De Bragança Pereira
Download or read book Data Science written by Carlos Alberto De Bragança Pereira and published by MDPI. This book was released on 2021-09-02 with total page 256 pages. Available in PDF, EPUB and Kindle. Book excerpt: With the increase in data processing and storage capacity, a large amount of data is available. Data without analysis does not have much value. Thus, the demand for data analysis is increasing daily, and the consequence is the appearance of a large number of jobs and published articles. Data science has emerged as a multidisciplinary field to support data-driven activities, integrating and developing ideas, methods, and processes to extract information from data. This includes methods built from different knowledge areas: Statistics, Computer Science, Mathematics, Physics, Information Science, and Engineering. This mixture of areas has given rise to what we call Data Science. New solutions to the new problems are reproducing rapidly to generate large volumes of data. Current and future challenges require greater care in creating new solutions that satisfy the rationality for each type of problem. Labels such as Big Data, Data Science, Machine Learning, Statistical Learning, and Artificial Intelligence are demanding more sophistication in the foundations and how they are being applied. This point highlights the importance of building the foundations of Data Science. This book is dedicated to solutions and discussions of measuring uncertainties in data analysis problems.
Book Synopsis Pattern Recognition and Computer Vision by : Zhouchen Lin
Download or read book Pattern Recognition and Computer Vision written by Zhouchen Lin and published by Springer Nature. This book was released on with total page 595 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Proceedings of the 2015 Chinese Intelligent Automation Conference by : Zhidong Deng
Download or read book Proceedings of the 2015 Chinese Intelligent Automation Conference written by Zhidong Deng and published by Springer. This book was released on 2015-04-20 with total page 570 pages. Available in PDF, EPUB and Kindle. Book excerpt: Proceedings of the 2015 Chinese Intelligent Automation Conference presents selected research papers from the CIAC’15, held in Fuzhou, China. The topics include adaptive control, fuzzy control, neural network based control, knowledge based control, hybrid intelligent control, learning control, evolutionary mechanism based control, multi-sensor integration, failure diagnosis, reconfigurable control, etc. Engineers and researchers from academia, industry and the government can gain valuable insights into interdisciplinary solutions in the field of intelligent automation.
Book Synopsis Medical Image Computing and Computer-Assisted Intervention − MICCAI 2017 by : Maxime Descoteaux
Download or read book Medical Image Computing and Computer-Assisted Intervention − MICCAI 2017 written by Maxime Descoteaux and published by Springer. This book was released on 2017-09-03 with total page 803 pages. Available in PDF, EPUB and Kindle. Book excerpt: The three-volume set LNCS 10433, 10434, and 10435 constitutes the refereed proceedings of the 20th International Conference on Medical Image Computing and Computer-Assisted Intervention, MICCAI 2017, held inQuebec City, Canada, in September 2017. The 255 revised full papers presented were carefully reviewed and selected from 800 submissions in a two-phase review process. The papers have been organized in the following topical sections: Part I: atlas and surface-based techniques; shape and patch-based techniques; registration techniques, functional imaging, connectivity, and brain parcellation; diffusion magnetic resonance imaging (dMRI) and tensor/fiber processing; and image segmentation and modelling. Part II: optical imaging; airway and vessel analysis; motion and cardiac analysis; tumor processing; planning and simulation for medical interventions; interventional imaging and navigation; and medical image computing. Part III: feature extraction and classification techniques; and machine learning in medical image computing.
Book Synopsis Advances in Machine Learning by : Zhi-Hua Zhou
Download or read book Advances in Machine Learning written by Zhi-Hua Zhou and published by Springer. This book was released on 2009-11-03 with total page 426 pages. Available in PDF, EPUB and Kindle. Book excerpt: The First Asian Conference on Machine Learning (ACML 2009) was held at Nanjing, China during November 2–4, 2009.This was the ?rst edition of a series of annual conferences which aim to provide a leading international forum for researchers in machine learning and related ?elds to share their new ideas and research ?ndings. This year we received 113 submissions from 18 countries and regions in Asia, Australasia, Europe and North America. The submissions went through a r- orous double-blind reviewing process. Most submissions received four reviews, a few submissions received ?ve reviews, while only several submissions received three reviews. Each submission was handled by an Area Chair who coordinated discussions among reviewers and made recommendation on the submission. The Program Committee Chairs examined the reviews and meta-reviews to further guarantee the reliability and integrity of the reviewing process. Twenty-nine - pers were selected after this process. To ensure that important revisions required by reviewers were incorporated into the ?nal accepted papers, and to allow submissions which would have - tential after a careful revision, this year we launched a “revision double-check” process. In short, the above-mentioned 29 papers were conditionally accepted, and the authors were requested to incorporate the “important-and-must”re- sionssummarizedbyareachairsbasedonreviewers’comments.Therevised?nal version and the revision list of each conditionally accepted paper was examined by the Area Chair and Program Committee Chairs. Papers that failed to pass the examination were ?nally rejected.
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 Cyber-Enabled Intelligence by : Huansheng Ning
Download or read book Cyber-Enabled Intelligence written by Huansheng Ning and published by Taylor & Francis. This book was released on 2019-08-08 with total page 355 pages. Available in PDF, EPUB and Kindle. Book excerpt: The book provides an advanced vision and trends of computational intelligence in cyberspace and cyber-enabled spaces. It reviews architectures and models, as well as state-of-the-art computational and interpretation capabilities for social, industrial, and multimedia applications. Cyber-enabled intelligence involves the design and development of intelligent and innovative application scenarios in social networks, computer vision, multimedia, and image processing. Application scenarios can also cover the applicability of intelligent sensing, data collection and predictive analysis in Internet of Things.
Book Synopsis Deep Learning in Computer Vision by : Mahmoud Hassaballah
Download or read book Deep Learning in Computer Vision written by Mahmoud Hassaballah and published by CRC Press. This book was released on 2020-03-23 with total page 339 pages. Available in PDF, EPUB and Kindle. Book excerpt: Deep learning algorithms have brought a revolution to the computer vision community by introducing non-traditional and efficient solutions to several image-related problems that had long remained unsolved or partially addressed. This book presents a collection of eleven chapters where each individual chapter explains the deep learning principles of a specific topic, introduces reviews of up-to-date techniques, and presents research findings to the computer vision community. The book covers a broad scope of topics in deep learning concepts and applications such as accelerating the convolutional neural network inference on field-programmable gate arrays, fire detection in surveillance applications, face recognition, action and activity recognition, semantic segmentation for autonomous driving, aerial imagery registration, robot vision, tumor detection, and skin lesion segmentation as well as skin melanoma classification. The content of this book has been organized such that each chapter can be read independently from the others. The book is a valuable companion for researchers, for postgraduate and possibly senior undergraduate students who are taking an advanced course in related topics, and for those who are interested in deep learning with applications in computer vision, image processing, and pattern recognition.
Book Synopsis Riemannian Computing in Computer Vision by : Pavan K. Turaga
Download or read book Riemannian Computing in Computer Vision written by Pavan K. Turaga and published by Springer. This book was released on 2015-11-09 with total page 382 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book presents a comprehensive treatise on Riemannian geometric computations and related statistical inferences in several computer vision problems. This edited volume includes chapter contributions from leading figures in the field of computer vision who are applying Riemannian geometric approaches in problems such as face recognition, activity recognition, object detection, biomedical image analysis, and structure-from-motion. Some of the mathematical entities that necessitate a geometric analysis include rotation matrices (e.g. in modeling camera motion), stick figures (e.g. for activity recognition), subspace comparisons (e.g. in face recognition), symmetric positive-definite matrices (e.g. in diffusion tensor imaging), and function-spaces (e.g. in studying shapes of closed contours).
Book Synopsis Graph-Based Representations in Pattern Recognition by : Cheng-Lin Liu
Download or read book Graph-Based Representations in Pattern Recognition written by Cheng-Lin Liu and published by Springer. This book was released on 2015-05-04 with total page 382 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the refereed proceedings of the 10th IAPR-TC-15 International Workshop on Graph-Based Representations in Pattern Recognition, GbRPR 2015, held in Beijing, China, in May 2015. The 36 papers presented in this volume were carefully reviewed and selected from 53 submissions. The accepted papers cover diverse issues of graph-based methods and applications, with 7 in graph representation, 15 in graph matching, 7 in graph clustering and classification, and 7 in graph-based applications.
Book Synopsis Machine Learning and Cybernetics by : Xizhao Wang
Download or read book Machine Learning and Cybernetics written by Xizhao Wang and published by Springer. This book was released on 2014-12-04 with total page 460 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the refereed proceedings of the 13th International Conference on Machine Learning and Cybernetics, Lanzhou, China, in July 2014. The 45 revised full papers presented were carefully reviewed and selected from 421 submissions. The papers are organized in topical sections on classification and semi-supervised learning; clustering and kernel; application to recognition; sampling and big data; application to detection; decision tree learning; learning and adaptation; similarity and decision making; learning with uncertainty; improved learning algorithms and applications.
Book Synopsis Information Theoretic Learning by : Jose C. Principe
Download or read book Information Theoretic Learning written by Jose C. Principe and published by Springer Science & Business Media. This book was released on 2010-04-06 with total page 538 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book is the first cohesive treatment of ITL algorithms to adapt linear or nonlinear learning machines both in supervised and unsupervised paradigms. It compares the performance of ITL algorithms with the second order counterparts in many applications.
Book Synopsis Impact of Scientific Computing on Science and Society by : Pekka Neittaanmäki
Download or read book Impact of Scientific Computing on Science and Society written by Pekka Neittaanmäki and published by Springer Nature. This book was released on 2023-07-07 with total page 451 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book analyzes the impact of scientific computing in science and society over the coming decades. It presents advanced methods that can provide new possibilities to solve scientific problems and study important phenomena in society. The chapters cover Scientific computing as the third paradigm of science as well as the impact of scientific computing on natural sciences, environmental science, economics, social science, humanistic science, medicine, and engineering. Moreover, the book investigates scientific computing in high performance computing, quantum computing, and artificial intelligence environment and what it will be like in the 2030s and 2040s.
