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2013 Ieee International Workshop On Machine Learning For Signal Processing Mlsp
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Book Synopsis 2013 IEEE International Workshop on Machine Learning for Signal Processing (MLSP) by : IEEE Staff
Download or read book 2013 IEEE International Workshop on Machine Learning for Signal Processing (MLSP) written by IEEE Staff and published by . This book was released on 2013-09-22 with total page 591 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Machine Learning for Signal Processing (MLSP 2006) and Life System Modelling, Simulation, and Bio-inspired Computing (LSMS 2007) ; [... Selection of Extended Versions of Papers that Have Originally Been Presented at the 2006 IEEE International Workshop on Machine Learning for Signal Processing (MLSP2006) in Maynooth, Ireland (September 6 - 8) (formerly Called the IEEE International Workshop on Neural Networks for Signal Processing, NNSP) ; ... Selection of 11 Previously Unpublished Papers ... to the 2007 International Conference on Life System Modeling and Simulation (LSMS'07), Held on 14 - 17 September 2007 in Shanghai, China] by : Marc M. Van Hulle
Download or read book Machine Learning for Signal Processing (MLSP 2006) and Life System Modelling, Simulation, and Bio-inspired Computing (LSMS 2007) ; [... Selection of Extended Versions of Papers that Have Originally Been Presented at the 2006 IEEE International Workshop on Machine Learning for Signal Processing (MLSP2006) in Maynooth, Ireland (September 6 - 8) (formerly Called the IEEE International Workshop on Neural Networks for Signal Processing, NNSP) ; ... Selection of 11 Previously Unpublished Papers ... to the 2007 International Conference on Life System Modeling and Simulation (LSMS'07), Held on 14 - 17 September 2007 in Shanghai, China] written by Marc M. Van Hulle and published by . This book was released on 2008 with total page 217 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Proceedings of International Conference on Machine Intelligence and Data Science Applications by : Manish Prateek
Download or read book Proceedings of International Conference on Machine Intelligence and Data Science Applications written by Manish Prateek and published by Springer Nature. This book was released on 2021 with total page 813 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book is a compilation of peer-reviewed papers presented at the International Conference on Machine Intelligence and Data Science Applications, organized by the School of Computer Science, University of Petroleum & Energy Studies, Dehradun, on September 4 and 5, 2020. The book starts by addressing the algorithmic aspect of machine intelligence which includes the framework and optimization of various states of algorithms. Variety of papers related to wide applications in various fields like image processing, natural language processing, computer vision, sentiment analysis, and speech and gesture analysis have been included with upfront details. The book concludes with interdisciplinary applications like legal, health care, smart society, cyber physical system and smart agriculture. The book is a good reference for computer science engineers, lecturers/researchers in machine intelligence discipline and engineering graduates.
Book Synopsis Machine Learning for Signal Processing XIX by :
Download or read book Machine Learning for Signal Processing XIX written by and published by . This book was released on 2009 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Machine Learning with Noisy Labels by : Gustavo Carneiro
Download or read book Machine Learning with Noisy Labels written by Gustavo Carneiro and published by Elsevier. This book was released on 2024-03-01 with total page 314 pages. Available in PDF, EPUB and Kindle. Book excerpt: Most of the modern machine learning models, based on deep learning techniques, depend on carefully curated and cleanly labelled training sets to be reliably trained and deployed. However, the expensive labelling process involved in the acquisition of such training sets limits the number and size of datasets available to build new models, slowing down progress in the field. Alternatively, many poorly curated training sets containing noisy labels are readily available to be used to build new models. However, the successful exploration of such noisy-label training sets depends on the development of algorithms and models that are robust to these noisy labels. Machine learning and Noisy Labels: Definitions, Theory, Techniques and Solutions defines different types of label noise, introduces the theory behind the problem, presents the main techniques that enable the effective use of noisy-label training sets, and explains the most accurate methods developed in the field. This book is an ideal introduction to machine learning with noisy labels suitable for senior undergraduates, post graduate students, researchers and practitioners using, and researching into, machine learning methods. Shows how to design and reproduce regression, classification and segmentation models using large-scale noisy-label training sets Gives an understanding of the theory of, and motivation for, noisy-label learning Shows how to classify noisy-label learning methods into a set of core techniques
Book Synopsis Signal Processing and Machine Learning Theory by : Paulo S.R. Diniz
Download or read book Signal Processing and Machine Learning Theory written by Paulo S.R. Diniz and published by Elsevier. This book was released on 2023-07-10 with total page 1236 pages. Available in PDF, EPUB and Kindle. Book excerpt: Signal Processing and Machine Learning Theory, authored by world-leading experts, reviews the principles, methods and techniques of essential and advanced signal processing theory. These theories and tools are the driving engines of many current and emerging research topics and technologies, such as machine learning, autonomous vehicles, the internet of things, future wireless communications, medical imaging, etc. Provides quick tutorial reviews of important and emerging topics of research in signal processing-based tools Presents core principles in signal processing theory and shows their applications Discusses some emerging signal processing tools applied in machine learning methods References content on core principles, technologies, algorithms and applications Includes references to journal articles and other literature on which to build further, more specific, and detailed knowledge
Book Synopsis Proceedings of Third International Conference on Sustainable Computing by : Ramesh Chandra Poonia
Download or read book Proceedings of Third International Conference on Sustainable Computing written by Ramesh Chandra Poonia and published by Springer Nature. This book was released on 2022-01-04 with total page 588 pages. Available in PDF, EPUB and Kindle. Book excerpt: The book includes a selection of the best papers presented at the Third International Conference on Sustainable Computing (SUSCOM 2021), held in Jaipur, India, during 19 – 20 March 2021. It covers topics like Internet of things (IoT); artificial system of security; smart storage and knowledge retrieval using data cloud; intelligent transport management; intelligent cognitive and bio-inspired computing and management science. The book is useful for peoples from academia, government bodies, healthcare and industry to discuss their future scope.
Book Synopsis Digital Signal Processing with Kernel Methods by : Jose Luis Rojo-Alvarez
Download or read book Digital Signal Processing with Kernel Methods written by Jose Luis Rojo-Alvarez and published by John Wiley & Sons. This book was released on 2018-02-05 with total page 665 pages. Available in PDF, EPUB and Kindle. Book excerpt: A realistic and comprehensive review of joint approaches to machine learning and signal processing algorithms, with application to communications, multimedia, and biomedical engineering systems Digital Signal Processing with Kernel Methods reviews the milestones in the mixing of classical digital signal processing models and advanced kernel machines statistical learning tools. It explains the fundamental concepts from both fields of machine learning and signal processing so that readers can quickly get up to speed in order to begin developing the concepts and application software in their own research. Digital Signal Processing with Kernel Methods provides a comprehensive overview of kernel methods in signal processing, without restriction to any application field. It also offers example applications and detailed benchmarking experiments with real and synthetic datasets throughout. Readers can find further worked examples with Matlab source code on a website developed by the authors: http://github.com/DSPKM • Presents the necessary basic ideas from both digital signal processing and machine learning concepts • Reviews the state-of-the-art in SVM algorithms for classification and detection problems in the context of signal processing • Surveys advances in kernel signal processing beyond SVM algorithms to present other highly relevant kernel methods for digital signal processing An excellent book for signal processing researchers and practitioners, Digital Signal Processing with Kernel Methods will also appeal to those involved in machine learning and pattern recognition.
Book Synopsis Artificial Intelligence for Environmental Sustainability and Green Initiatives by : Aboul Ella Hassanien
Download or read book Artificial Intelligence for Environmental Sustainability and Green Initiatives written by Aboul Ella Hassanien and published by Springer Nature. This book was released on with total page 361 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Green, Pervasive, and Cloud Computing by : Zhiwen Yu
Download or read book Green, Pervasive, and Cloud Computing written by Zhiwen Yu and published by Springer Nature. This book was released on 2020-12-04 with total page 519 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the refereed proceedings of the 15th International Conference on Green, Pervasive, and Cloud Computing, GPC 2020, held in Xi'an, China, in November 2020. The 30 full papers presented in this book together with 8 short papers were carefully reviewed and selected from 96 submissions. They cover the following topics: Device-free Sensing; Machine Learning; Recommendation Systems; Urban Computing; Human Computer Interaction; Internet of Things and Edge Computing; Positioning; Applications of Computer Vision; CrowdSensing; and Cloud and Related Technologies.
Book Synopsis Hardware-Aware Probabilistic Machine Learning Models by : Laura Isabel Galindez Olascoaga
Download or read book Hardware-Aware Probabilistic Machine Learning Models written by Laura Isabel Galindez Olascoaga and published by Springer Nature. This book was released on 2021-05-19 with total page 163 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book proposes probabilistic machine learning models that represent the hardware properties of the device hosting them. These models can be used to evaluate the impact that a specific device configuration may have on resource consumption and performance of the machine learning task, with the overarching goal of balancing the two optimally. The book first motivates extreme-edge computing in the context of the Internet of Things (IoT) paradigm. Then, it briefly reviews the steps involved in the execution of a machine learning task and identifies the implications associated with implementing this type of workload in resource-constrained devices. The core of this book focuses on augmenting and exploiting the properties of Bayesian Networks and Probabilistic Circuits in order to endow them with hardware-awareness. The proposed models can encode the properties of various device sub-systems that are typically not considered by other resource-aware strategies, bringing about resource-saving opportunities that traditional approaches fail to uncover. The performance of the proposed models and strategies is empirically evaluated for several use cases. All of the considered examples show the potential of attaining significant resource-saving opportunities with minimal accuracy losses at application time. Overall, this book constitutes a novel approach to hardware-algorithm co-optimization that further bridges the fields of Machine Learning and Electrical Engineering.
Book Synopsis Integrative Cluster Analysis in Bioinformatics by : Basel Abu-Jamous
Download or read book Integrative Cluster Analysis in Bioinformatics written by Basel Abu-Jamous and published by John Wiley & Sons. This book was released on 2015-06-15 with total page 451 pages. Available in PDF, EPUB and Kindle. Book excerpt: Clustering techniques are increasingly being put to use in the analysis of high-throughput biological datasets. Novel computational techniques to analyse high throughput data in the form of sequences, gene and protein expressions, pathways, and images are becoming vital for understanding diseases and future drug discovery. This book details the complete pathway of cluster analysis, from the basics of molecular biology to the generation of biological knowledge. The book also presents the latest clustering methods and clustering validation, thereby offering the reader a comprehensive review of clustering analysis in bioinformatics from the fundamentals through to state-of-the-art techniques and applications. Key Features: Offers a contemporary review of clustering methods and applications in the field of bioinformatics, with particular emphasis on gene expression analysis Provides an excellent introduction to molecular biology with computer scientists and information engineering researchers in mind, laying out the basic biological knowledge behind the application of clustering analysis techniques in bioinformatics Explains the structure and properties of many types of high-throughput datasets commonly found in biological studies Discusses how clustering methods and their possible successors would be used to enhance the pace of biological discoveries in the future Includes a companion website hosting a selected collection of codes and links to publicly available datasets
Book Synopsis Brain–Computer Interfaces Handbook by : Chang S. Nam
Download or read book Brain–Computer Interfaces Handbook written by Chang S. Nam and published by CRC Press. This book was released on 2018-01-09 with total page 1176 pages. Available in PDF, EPUB and Kindle. Book excerpt: Brain–Computer Interfaces Handbook: Technological and Theoretical Advances provides a tutorial and an overview of the rich and multi-faceted world of Brain–Computer Interfaces (BCIs). The authors supply readers with a contemporary presentation of fundamentals, theories, and diverse applications of BCI, creating a valuable resource for anyone involved with the improvement of people’s lives by replacing, restoring, improving, supplementing or enhancing natural output from the central nervous system. It is a useful guide for readers interested in understanding how neural bases for cognitive and sensory functions, such as seeing, hearing, and remembering, relate to real-world technologies. More precisely, this handbook details clinical, therapeutic and human-computer interfaces applications of BCI and various aspects of human cognition and behavior such as perception, affect, and action. It overviews the different methods and techniques used in acquiring and pre-processing brain signals, extracting features, and classifying users’ mental states and intentions. Various theories, models, and empirical findings regarding the ways in which the human brain interfaces with external systems and environments using BCI are also explored. The handbook concludes by engaging ethical considerations, open questions, and challenges that continue to face brain–computer interface research. Features an in-depth look at the different methods and techniques used in acquiring and pre-processing brain signals, extracting features, and classifying the user's intention Covers various theories, models, and empirical findings regarding ways in which the human brain can interface with the systems or external environments Presents applications of BCI technology to understand various aspects of human cognition and behavior such as perception, affect, action, and more Includes clinical trials and individual case studies of the experimental therapeutic applications of BCI Provides human factors and human-computer interface concerns in the design, development, and evaluation of BCIs Overall, this handbook provides a synopsis of key technological and theoretical advances that are directly applicable to brain–computer interfacing technologies and can be readily understood and applied by individuals with no formal training in BCI research and development.
Book Synopsis Advances in Multimedia Information Processing – PCM 2018 by : Richang Hong
Download or read book Advances in Multimedia Information Processing – PCM 2018 written by Richang Hong and published by Springer. This book was released on 2018-09-18 with total page 848 pages. Available in PDF, EPUB and Kindle. Book excerpt: The three-volume set LNCS 101164, 11165, and 11166 constitutes the refereed proceedings of the 19th Pacific-Rim Conference on Multimedia, PCM 2018, held in Hefei, China, in September 2018. The 209 regular papers presented together with 20 special session papers were carefully reviewed and selected from 452 submissions. The papers cover topics such as: multimedia content analysis; multimedia signal processing and communications; and multimedia applications and services.
Book Synopsis Machine Learning for Protein Subcellular Localization Prediction by : Shibiao Wan
Download or read book Machine Learning for Protein Subcellular Localization Prediction written by Shibiao Wan and published by Walter de Gruyter GmbH & Co KG. This book was released on 2015-05-19 with total page 210 pages. Available in PDF, EPUB and Kindle. Book excerpt: Comprehensively covers protein subcellular localization from single-label prediction to multi-label prediction, and includes prediction strategies for virus, plant, and eukaryote species. Three machine learning tools are introduced to improve classification refinement, feature extraction, and dimensionality reduction.
Book Synopsis Advances in Image and Graphics Technologies by : Tieniu Tan
Download or read book Advances in Image and Graphics Technologies written by Tieniu Tan and published by Springer. This book was released on 2016-08-08 with total page 259 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the refereed proceedings of the 11th Chinese Conference on Image and Graphics Technologies and Applications, IGTA 2016, held in Beijing, China in July 2016. The 27 papers presented were carefully reviewed and selected from 69 submissions. They provide a forum for sharing progresses in the areas of image processing technology; image analysis and understanding; computer vision and pattern recognition; big data mining, computer graphics and VR; as well as image technology applications.
Book Synopsis Music Data Analysis by : Claus Weihs
Download or read book Music Data Analysis written by Claus Weihs and published by CRC Press. This book was released on 2016-11-17 with total page 531 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book provides a comprehensive overview of music data analysis, from introductory material to advanced concepts. It covers various applications including transcription and segmentation as well as chord and harmony, instrument and tempo recognition. It also discusses the implementation aspects of music data analysis such as architecture, user interface and hardware. It is ideal for use in university classes with an interest in music data analysis. It also could be used in computer science and statistics as well as musicology.