2014 IEEE International Workshop on Machine Learning for Signal Processing (MLSP 2014)

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Publisher :
ISBN 13 : 9781479936953
Total Pages : 520 pages
Book Rating : 4.9/5 (369 download)

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Book Synopsis 2014 IEEE International Workshop on Machine Learning for Signal Processing (MLSP 2014) by :

Download or read book 2014 IEEE International Workshop on Machine Learning for Signal Processing (MLSP 2014) written by and published by . This book was released on 2014 with total page 520 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Proceedings of MLSP 2014

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Publisher :
ISBN 13 : 9781479936946
Total Pages : pages
Book Rating : 4.9/5 (369 download)

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Book Synopsis Proceedings of MLSP 2014 by : Mamadou Mboup

Download or read book Proceedings of MLSP 2014 written by Mamadou Mboup and published by . This book was released on 2014 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:

Signal Processing and Machine Learning for Biomedical Big Data

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Publisher : CRC Press
ISBN 13 : 1351061216
Total Pages : 1235 pages
Book Rating : 4.3/5 (51 download)

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Book Synopsis Signal Processing and Machine Learning for Biomedical Big Data by : Ervin Sejdic

Download or read book Signal Processing and Machine Learning for Biomedical Big Data written by Ervin Sejdic and published by CRC Press. This book was released on 2018-07-04 with total page 1235 pages. Available in PDF, EPUB and Kindle. Book excerpt: Within the healthcare domain, big data is defined as any ``high volume, high diversity biological, clinical, environmental, and lifestyle information collected from single individuals to large cohorts, in relation to their health and wellness status, at one or several time points.'' Such data is crucial because within it lies vast amounts of invaluable information that could potentially change a patient's life, opening doors to alternate therapies, drugs, and diagnostic tools. Signal Processing and Machine Learning for Biomedical Big Data thus discusses modalities; the numerous ways in which this data is captured via sensors; and various sample rates and dimensionalities. Capturing, analyzing, storing, and visualizing such massive data has required new shifts in signal processing paradigms and new ways of combining signal processing with machine learning tools. This book covers several of these aspects in two ways: firstly, through theoretical signal processing chapters where tools aimed at big data (be it biomedical or otherwise) are described; and, secondly, through application-driven chapters focusing on existing applications of signal processing and machine learning for big biomedical data. This text aimed at the curious researcher working in the field, as well as undergraduate and graduate students eager to learn how signal processing can help with big data analysis. It is the hope of Drs. Sejdic and Falk that this book will bring together signal processing and machine learning researchers to unlock existing bottlenecks within the healthcare field, thereby improving patient quality-of-life. Provides an overview of recent state-of-the-art signal processing and machine learning algorithms for biomedical big data, including applications in the neuroimaging, cardiac, retinal, genomic, sleep, patient outcome prediction, critical care, and rehabilitation domains. Provides contributed chapters from world leaders in the fields of big data and signal processing, covering topics such as data quality, data compression, statistical and graph signal processing techniques, and deep learning and their applications within the biomedical sphere. This book’s material covers how expert domain knowledge can be used to advance signal processing and machine learning for biomedical big data applications.

2014 International Conference on Artificial Intelligence and Software Engineering(AISE2014)

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Publisher : DEStech Publications, Inc
ISBN 13 : 1605951501
Total Pages : 665 pages
Book Rating : 4.6/5 (59 download)

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Book Synopsis 2014 International Conference on Artificial Intelligence and Software Engineering(AISE2014) by : S. K. Chen, Altair Engineering Inc., California, USA

Download or read book 2014 International Conference on Artificial Intelligence and Software Engineering(AISE2014) written by S. K. Chen, Altair Engineering Inc., California, USA and published by DEStech Publications, Inc. This book was released on 2014-02-06 with total page 665 pages. Available in PDF, EPUB and Kindle. Book excerpt: 2014 International Conference on Artificial Intelligence and Software Engineering(AISE2014) aims to provide a forum for accessing to the most up-to-date and authoritative knowledge from both Artificial Intelligence and Software Engineering. AISE2014 features unique mixed topics of AI Algorithms, Data Mining, Knowledge-based Systems, Software Process and so on. The goal of this conference is to bring researchers, engineers, and students to the areas of Artificial Intelligence and Software Engineering to share experiences and original research contributions on those topics. Researchers and practitioners are invited to submit their contributions to AISE2014.

Source Separation and Machine Learning

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Publisher : Academic Press
ISBN 13 : 0128045779
Total Pages : 386 pages
Book Rating : 4.1/5 (28 download)

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Book Synopsis Source Separation and Machine Learning by : Jen-Tzung Chien

Download or read book Source Separation and Machine Learning written by Jen-Tzung Chien and published by Academic Press. This book was released on 2018-10-16 with total page 386 pages. Available in PDF, EPUB and Kindle. Book excerpt: Source Separation and Machine Learning presents the fundamentals in adaptive learning algorithms for Blind Source Separation (BSS) and emphasizes the importance of machine learning perspectives. It illustrates how BSS problems are tackled through adaptive learning algorithms and model-based approaches using the latest information on mixture signals to build a BSS model that is seen as a statistical model for a whole system. Looking at different models, including independent component analysis (ICA), nonnegative matrix factorization (NMF), nonnegative tensor factorization (NTF), and deep neural network (DNN), the book addresses how they have evolved to deal with multichannel and single-channel source separation. Emphasizes the modern model-based Blind Source Separation (BSS) which closely connects the latest research topics of BSS and Machine Learning Includes coverage of Bayesian learning, sparse learning, online learning, discriminative learning and deep learning Presents a number of case studies of model-based BSS (categorizing them into four modern models - ICA, NMF, NTF and DNN), using a variety of learning algorithms that provide solutions for the construction of BSS systems

Advances in Informatics and Computing in Civil and Construction Engineering

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Publisher : Springer
ISBN 13 : 3030002209
Total Pages : 886 pages
Book Rating : 4.0/5 (3 download)

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Book Synopsis Advances in Informatics and Computing in Civil and Construction Engineering by : Ivan Mutis

Download or read book Advances in Informatics and Computing in Civil and Construction Engineering written by Ivan Mutis and published by Springer. This book was released on 2018-10-08 with total page 886 pages. Available in PDF, EPUB and Kindle. Book excerpt: This proceedings volume chronicles the papers presented at the 35th CIB W78 2018 Conference: IT in Design, Construction, and Management, held in Chicago, IL, USA, in October 2018. The theme of the conference focused on fostering, encouraging, and promoting research and development in the application of integrated information technology (IT) throughout the life-cycle of the design, construction, and occupancy of buildings and related facilities. The CIB – International Council for Research and Innovation in Building Construction – was established in 1953 as an association whose objectives were to stimulate and facilitate international cooperation and information exchange between governmental research institutes in the building and construction sector, with an emphasis on those institutes engaged in technical fields of research. The conference brought together more than 200 scholars from 40 countries, who presented the innovative concepts and methods featured in this collection of papers.

Audio Source Separation

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Publisher : Springer
ISBN 13 : 3319730312
Total Pages : 389 pages
Book Rating : 4.3/5 (197 download)

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Book Synopsis Audio Source Separation by : Shoji Makino

Download or read book Audio Source Separation written by Shoji Makino and published by Springer. This book was released on 2018-03-01 with total page 389 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book provides the first comprehensive overview of the fascinating topic of audio source separation based on non-negative matrix factorization, deep neural networks, and sparse component analysis. The first section of the book covers single channel source separation based on non-negative matrix factorization (NMF). After an introduction to the technique, two further chapters describe separation of known sources using non-negative spectrogram factorization, and temporal NMF models. In section two, NMF methods are extended to multi-channel source separation. Section three introduces deep neural network (DNN) techniques, with chapters on multichannel and single channel separation, and a further chapter on DNN based mask estimation for monaural speech separation. In section four, sparse component analysis (SCA) is discussed, with chapters on source separation using audio directional statistics modelling, multi-microphone MMSE-based techniques and diffusion map methods. The book brings together leading researchers to provide tutorial-like and in-depth treatments on major audio source separation topics, with the objective of becoming the definitive source for a comprehensive, authoritative, and accessible treatment. This book is written for graduate students and researchers who are interested in audio source separation techniques based on NMF, DNN and SCA.

Nonlinear Programming

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Publisher : Athena Scientific
ISBN 13 : 1886529051
Total Pages : 1100 pages
Book Rating : 4.8/5 (865 download)

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Book Synopsis Nonlinear Programming by : Dimitri Bertsekas

Download or read book Nonlinear Programming written by Dimitri Bertsekas and published by Athena Scientific. This book was released on 2016-09-01 with total page 1100 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book provides a comprehensive and accessible presentation of algorithms for solving continuous optimization problems. It relies on rigorous mathematical analysis, but also aims at an intuitive exposition that makes use of visualization where possible. It places particular emphasis on modern developments, and their widespread applications in fields such as large-scale resource allocation problems, signal processing, and machine learning. The 3rd edition brings the book in closer harmony with the companion works Convex Optimization Theory (Athena Scientific, 2009), Convex Optimization Algorithms (Athena Scientific, 2015), Convex Analysis and Optimization (Athena Scientific, 2003), and Network Optimization (Athena Scientific, 1998). These works are complementary in that they deal primarily with convex, possibly nondifferentiable, optimization problems and rely on convex analysis. By contrast the nonlinear programming book focuses primarily on analytical and computational methods for possibly nonconvex differentiable problems. It relies primarily on calculus and variational analysis, yet it still contains a detailed presentation of duality theory and its uses for both convex and nonconvex problems. This on-line edition contains detailed solutions to all the theoretical book exercises. Among its special features, the book: Provides extensive coverage of iterative optimization methods within a unifying framework Covers in depth duality theory from both a variational and a geometric point of view Provides a detailed treatment of interior point methods for linear programming Includes much new material on a number of topics, such as proximal algorithms, alternating direction methods of multipliers, and conic programming Focuses on large-scale optimization topics of much current interest, such as first order methods, incremental methods, and distributed asynchronous computation, and their applications in machine learning, signal processing, neural network training, and big data applications Includes a large number of examples and exercises Was developed through extensive classroom use in first-year graduate courses

Optical Fiber Sensors for the Next Generation of Rehabilitation Robotics

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Publisher : Academic Press
ISBN 13 : 0323903495
Total Pages : 318 pages
Book Rating : 4.3/5 (239 download)

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Book Synopsis Optical Fiber Sensors for the Next Generation of Rehabilitation Robotics by : Arnaldo Leal-Junior

Download or read book Optical Fiber Sensors for the Next Generation of Rehabilitation Robotics written by Arnaldo Leal-Junior and published by Academic Press. This book was released on 2021-10-26 with total page 318 pages. Available in PDF, EPUB and Kindle. Book excerpt: Optical Fiber Sensors for the Next Generation of Rehabilitation Robotics presents development concepts and applications of optical fiber sensors made of compliant materials in rehabilitation robotics. The book provides methods for the instrumentation of novel compliant devices. It presents the development, characterization and application of optical fiber sensors in robotics, ranging from conventional robots with rigid structures to novel wearable systems with soft structures, including smart textiles and intelligent structures for healthcare. Readers can look to this book for help in designing robotic structures for different applications, including problem-solving tactics in soft robotics. This book will be a great resource for mechanical, electrical and electronics engineers and photonics and optical sensing engineers. Addresses optical fiber sensing solutions in wearable systems and soft robotics Presents developments—from foundational, to novel and future applications—of optical fiber sensors in the next generation of robotic devices Provides methods for the instrumentation of novel compliant devices

Computer Vision – ECCV 2018

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Publisher : Springer
ISBN 13 : 3030012492
Total Pages : 880 pages
Book Rating : 4.0/5 (3 download)

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Book Synopsis Computer Vision – ECCV 2018 by : Vittorio Ferrari

Download or read book Computer Vision – ECCV 2018 written by Vittorio Ferrari and published by Springer. This book was released on 2018-10-05 with total page 880 pages. Available in PDF, EPUB and Kindle. Book excerpt: The sixteen-volume set comprising the LNCS volumes 11205-11220 constitutes the refereed proceedings of the 15th European Conference on Computer Vision, ECCV 2018, held in Munich, Germany, in September 2018.The 776 revised papers presented were carefully reviewed and selected from 2439 submissions. The papers are organized in topical sections on learning for vision; computational photography; human analysis; human sensing; stereo and reconstruction; optimization; matching and recognition; video attention; and poster sessions.

Cooperative and Graph Signal Processing

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Publisher : Academic Press
ISBN 13 : 0128136782
Total Pages : 868 pages
Book Rating : 4.1/5 (281 download)

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Book Synopsis Cooperative and Graph Signal Processing by : Petar Djuric

Download or read book Cooperative and Graph Signal Processing written by Petar Djuric and published by Academic Press. This book was released on 2018-07-04 with total page 868 pages. Available in PDF, EPUB and Kindle. Book excerpt: Cooperative and Graph Signal Processing: Principles and Applications presents the fundamentals of signal processing over networks and the latest advances in graph signal processing. A range of key concepts are clearly explained, including learning, adaptation, optimization, control, inference and machine learning. Building on the principles of these areas, the book then shows how they are relevant to understanding distributed communication, networking and sensing and social networks. Finally, the book shows how the principles are applied to a range of applications, such as Big data, Media and video, Smart grids, Internet of Things, Wireless health and Neuroscience. With this book readers will learn the basics of adaptation and learning in networks, the essentials of detection, estimation and filtering, Bayesian inference in networks, optimization and control, machine learning, signal processing on graphs, signal processing for distributed communication, social networks from the perspective of flow of information, and how to apply signal processing methods in distributed settings. Presents the first book on cooperative signal processing and graph signal processing Provides a range of applications and application areas that are thoroughly covered Includes an editor in chief and associate editor from the IEEE Transactions on Signal Processing and Information Processing over Networks who have recruited top contributors for the book

Dynamic Neural Networks for Robot Systems: Data-Driven and Model-Based Applications

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Publisher : Frontiers Media SA
ISBN 13 : 2832552013
Total Pages : 301 pages
Book Rating : 4.8/5 (325 download)

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Book Synopsis Dynamic Neural Networks for Robot Systems: Data-Driven and Model-Based Applications by : Long Jin

Download or read book Dynamic Neural Networks for Robot Systems: Data-Driven and Model-Based Applications written by Long Jin and published by Frontiers Media SA. This book was released on 2024-07-24 with total page 301 pages. Available in PDF, EPUB and Kindle. Book excerpt: Neural network control has been a research hotspot in academic fields due to the strong ability of computation. One of its wildly applied fields is robotics. In recent years, plenty of researchers have devised different types of dynamic neural network (DNN) to address complex control issues in robotics fields in reality. Redundant manipulators are no doubt indispensable devices in industrial production. There are various works on the redundancy resolution of redundant manipulators in performing a given task with the manipulator model information known. However, it becomes knotty for researchers to precisely control redundant manipulators with unknown model to complete a cyclic-motion generation CMG task, to some extent. It is worthwhile to investigate the data-driven scheme and the corresponding novel dynamic neural network (DNN), which exploits learning and control simultaneously. Therefore, it is of great significance to further research the special control features and solve challenging issues to improve control performance from several perspectives, such as accuracy, robustness, and solving speed.

Advances in Computing and Data Sciences

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Publisher : Springer Nature
ISBN 13 : 3031126416
Total Pages : 464 pages
Book Rating : 4.0/5 (311 download)

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Book Synopsis Advances in Computing and Data Sciences by : Mayank Singh

Download or read book Advances in Computing and Data Sciences written by Mayank Singh and published by Springer Nature. This book was released on 2022-07-26 with total page 464 pages. Available in PDF, EPUB and Kindle. Book excerpt: The two-volume proceedings CCIS 1613 + 1614 constitute revised selected papers from the 6th International Conference on Advances in Computing and Data Sciences, ICACDS 2022, which was held in Kurnool, India in April 2022. The total of 69 full papers presented in the proceedings was carefully reviewed and selected from 411 submissions. The papers focus on advances of next generation computing technologies in the areas of advanced computing and data sciences.

Advances in Biometrics

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Publisher : Springer Nature
ISBN 13 : 3030304361
Total Pages : 360 pages
Book Rating : 4.0/5 (33 download)

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Book Synopsis Advances in Biometrics by : G.R. Sinha

Download or read book Advances in Biometrics written by G.R. Sinha and published by Springer Nature. This book was released on 2019-12-13 with total page 360 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book provides a framework for robust and novel biometric techniques, along with implementation and design strategies. The theory, principles, pragmatic and modern methods, and future directions of biometrics are presented, along with in-depth coverage of biometric applications in driverless cars, automated and AI-based systems, IoT, and wearable devices. Additional coverage includes computer vision and pattern recognition, cybersecurity, cognitive computing, soft biometrics, and the social impact of biometric technology. The book will be a valuable reference for researchers, faculty, and practicing professionals working in biometrics and related fields, such as image processing, computer vision, and artificial intelligence. Highlights robust and novel biometrics techniques Provides implementation strategies and future research directions in the field of biometrics Includes case studies and emerging applications

Latent Variable Analysis and Signal Separation

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Publisher : Springer
ISBN 13 : 3319224824
Total Pages : 534 pages
Book Rating : 4.3/5 (192 download)

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Book Synopsis Latent Variable Analysis and Signal Separation by : Emmanuel Vincent

Download or read book Latent Variable Analysis and Signal Separation written by Emmanuel Vincent and published by Springer. This book was released on 2015-08-14 with total page 534 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the proceedings of the 12th International Conference on Latent Variable Analysis and Signal Separation, LVA/ICS 2015, held in Liberec, Czech Republic, in August 2015. The 61 revised full papers presented – 29 accepted as oral presentations and 32 accepted as poster presentations – were carefully reviewed and selected from numerous submissions. Five special topics are addressed: tensor-based methods for blind signal separation; deep neural networks for supervised speech separation/enhancement; joined analysis of multiple datasets, data fusion, and related topics; advances in nonlinear blind source separation; sparse and low rank modeling for acoustic signal processing.

Multi-faceted Deep Learning

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Publisher : Springer Nature
ISBN 13 : 3030744787
Total Pages : 321 pages
Book Rating : 4.0/5 (37 download)

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Book Synopsis Multi-faceted Deep Learning by : Jenny Benois-Pineau

Download or read book Multi-faceted Deep Learning written by Jenny Benois-Pineau and published by Springer Nature. This book was released on 2021-10-20 with total page 321 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book covers a large set of methods in the field of Artificial Intelligence - Deep Learning applied to real-world problems. The fundamentals of the Deep Learning approach and different types of Deep Neural Networks (DNNs) are first summarized in this book, which offers a comprehensive preamble for further problem–oriented chapters. The most interesting and open problems of machine learning in the framework of Deep Learning are discussed in this book and solutions are proposed. This book illustrates how to implement the zero-shot learning with Deep Neural Network Classifiers, which require a large amount of training data. The lack of annotated training data naturally pushes the researchers to implement low supervision algorithms. Metric learning is a long-term research but in the framework of Deep Learning approaches, it gets freshness and originality. Fine-grained classification with a low inter-class variability is a difficult problem for any classification tasks. This book presents how it is solved, by using different modalities and attention mechanisms in 3D convolutional networks. Researchers focused on Machine Learning, Deep learning, Multimedia and Computer Vision will want to buy this book. Advanced level students studying computer science within these topic areas will also find this book useful.

Hybrid Artificial Intelligent Systems

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Publisher : Springer
ISBN 13 : 331992639X
Total Pages : 765 pages
Book Rating : 4.3/5 (199 download)

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Book Synopsis Hybrid Artificial Intelligent Systems by : Francisco Javier de Cos Juez

Download or read book Hybrid Artificial Intelligent Systems written by Francisco Javier de Cos Juez and published by Springer. This book was released on 2018-06-09 with total page 765 pages. Available in PDF, EPUB and Kindle. Book excerpt: This volume constitutes the refereed proceedings of the 13th International Conference on Hybrid Artificial Intelligent Systems, HAIS 2018, held in Oviedo, Spain, in June 2018. The 62 full papers published in this volume were carefully reviewed and selected from 104 submissions. They are organized in the following topical sections: Neurocomputing, fuzzy systems, rough sets, evolutionary algorithms, Agents andMultiagent Systems, and alike.