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EBookClubs

Read Books & Download eBooks Full Online

Book 2016 IEEE 26th International Workshop on Machine Learning for Signal Processing  MLSP

Download or read book 2016 IEEE 26th International Workshop on Machine Learning for Signal Processing MLSP written by IEEE Staff and published by . This book was released on 2016-09-13 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: Bring together reaserchers from the signal processing society and the wider machine learning community to a common forum

Book 2017 IEEE 27th International Workshop on Machine Learning for Signal Processing  MLSP

Download or read book 2017 IEEE 27th International Workshop on Machine Learning for Signal Processing MLSP written by IEEE Staff and published by . This book was released on 2017-09-25 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: Bring together researchers from the signal processing society and the wider machine learning community to a common forum

Book Digital Signal Processing with Kernel Methods

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 Soft Computing and Signal Processing

Download or read book Soft Computing and Signal Processing written by V. Sivakumar Reddy and published by Springer Nature. This book was released on 2021-05-20 with total page 729 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book presents selected research papers on current developments in the fields of soft computing and signal processing from the Third International Conference on Soft Computing and Signal Processing (ICSCSP 2020). The book covers topics such as soft sets, rough sets, fuzzy logic, neural networks, genetic algorithms and machine learning and discusses various aspects of these topics, e.g., technological considerations, product implementation and application issues.

Book Advances in Signal Processing and Intelligent Recognition Systems

Download or read book Advances in Signal Processing and Intelligent Recognition Systems written by Sabu M. Thampi and published by Springer. This book was released on 2019-01-05 with total page 466 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the refereed proceedings of the 4th International Symposium on Advances in Signal Processing and Intelligent Recognition Systems, SIRS 2018, held in Bangalore, India, in September 2018. The 28 revised full papers and 11 revised short papers presented were carefully reviewed and selected from 92 submissions. The papers cover wide research fields including information retrieval, human-computer interaction (HCI), information extraction, speech recognition.

Book Modelling  Simulation and Applications of Complex Systems

Download or read book Modelling Simulation and Applications of Complex Systems written by Mohd Hafiz Mohd and published by Springer Nature. This book was released on 2021-06-10 with total page 440 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book discusses the latest progresses and developments on complex systems research and intends to give an exposure to prospective readers about the theoretical and practical aspects of mathematical modelling, numerical simulation and agent-based modelling frameworks. The main purpose of this book is to emphasize a unified approach to complex systems analysis, which goes beyond to examine complicated phenomena of numerous real-life systems; this is done by investigating a huge number of components that interact with each other at different (microscopic and macroscopic) scales; new insights and emergent collective behaviours can evolve from the interactions between individual components and also with their environments. These tools and concepts permit us to better understand the patterns of various real-life systems and help us to comprehend the mechanisms behind which distinct factors shaping some complex systems phenomena being influenced. This book is published in conjunction with the International Workshop on Complex Systems Modelling & Simulation 2019 (CoSMoS 2019): IoT & Big Data Integration. This international event was held at the Universiti Sains Malaysia Main Campus, Penang, Malaysia, from 8 to 11 April 2019. This book appeals to readers interested in complex systems research and other related areas such as mathematical modelling, numerical simulation and agent-based modelling frameworks.

Book Machine Learning and Knowledge Extraction

Download or read book Machine Learning and Knowledge Extraction written by Andreas Holzinger and published by Springer Nature. This book was released on 2019-08-22 with total page 428 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the refereed proceedings of the IFIP TC 5, TC 12, WG 8.4, 8.9, 12.9 International Cross-Domain Conference for Machine Learning and Knowledge Extraction, CD-MAKE 2019, held in Canterbury, UK, in August 2019. The 25 revised full papers presented were carefully reviewed and selected from 45 submissions. The cross-domain integration and appraisal of different fields provides an atmosphere to foster different perspectives and opinions; it will offer a platform for novel ideas and a fresh look on the methodologies to put these ideas into business for the benefit of humanity.

Book Digital Libraries at Times of Massive Societal Transition

Download or read book Digital Libraries at Times of Massive Societal Transition written by Emi Ishita and published by Springer Nature. This book was released on 2020-11-27 with total page 424 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the refereed proceedings of the 22nd International Conference on Asia-Pacific Digital Libraries, ICADL 2020, which was planned to be held in Kyoto, Japan, in November/December 2020, but it was held virtually due to the COVID-19 pandemic. The 10 full, 15 short, 4 practitioners, and 10 work-in-progress papers presented in this volume were carefully reviewed and selected from 79 submissions. The papers were organized in topical sections named: natural language processing; knowledge structures; citation data analysis; user analytics; application of cultural and historical data; social media; metadata and infrastructure; and scholarly data mining.

Book Neural Advances in Processing Nonlinear Dynamic Signals

Download or read book Neural Advances in Processing Nonlinear Dynamic Signals written by Anna Esposito and published by Springer. This book was released on 2018-07-21 with total page 318 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book proposes neural networks algorithms and advanced machine learning techniques for processing nonlinear dynamic signals such as audio, speech, financial signals, feedback loops, waveform generation, filtering, equalization, signals from arrays of sensors, and perturbations in the automatic control of industrial production processes. It also discusses the drastic changes in financial, economic, and work processes that are currently being experienced by the computational and engineering sciences community. Addresses key aspects, such as the integration of neural algorithms and procedures for the recognition, the analysis and detection of dynamic complex structures and the implementation of systems for discovering patterns in data, the book highlights the commonalities between computational intelligence (CI) and information and communications technologies (ICT) to promote transversal skills and sophisticated processing techniques. This book is a valuable resource for a. The academic research community b. The ICT market c. PhD students and early stage researchers d. Companies, research institutes e. Representatives from industry and standardization bodies

Book Machine Learning for Data Science Handbook

Download or read book Machine Learning for Data Science Handbook written by Lior Rokach and published by Springer Nature. This book was released on 2023-08-17 with total page 975 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book organizes key concepts, theories, standards, methodologies, trends, challenges and applications of data mining and knowledge discovery in databases. It first surveys, then provides comprehensive yet concise algorithmic descriptions of methods, including classic methods plus the extensions and novel methods developed recently. It also gives in-depth descriptions of data mining applications in various interdisciplinary industries.

Book Intelligent Systems

    Book Details:
  • Author : André Britto
  • Publisher : Springer Nature
  • Release : 2021-11-27
  • ISBN : 3030916995
  • Pages : 649 pages

Download or read book Intelligent Systems written by André Britto and published by Springer Nature. This book was released on 2021-11-27 with total page 649 pages. Available in PDF, EPUB and Kindle. Book excerpt: The two-volume set LNAI 13073 and 13074 constitutes the proceedings of the 10th Brazilian Conference on Intelligent Systems, BRACIS 2021, held in São Paolo, Brazil, in November-December 2021. The total of 77 papers presented in these two volumes was carefully reviewed and selected from 192 submissions.The contributions are organized in the following topical sections: Part I: Agent and Multi-Agent Systems, Planning and Reinforcement Learning; Evolutionary Computation, Metaheuristics, Constrains and Search, Combinatorial and Numerical Optimization, Knowledge Representation, Logic and Fuzzy Systems; Machine Learning and Data Mining. Part II: Multidisciplinary Artificial and Computational Intelligence and Applications; Neural Networks, Deep Learning and Computer Vision; Text Mining and Natural Language Processing. Due to the COVID-2019 pandemic, BRACIS 2021 was held as a virtual event.

Book Intelligent Systems

    Book Details:
  • Author : João Carlos Xavier-Junior
  • Publisher : Springer Nature
  • Release : 2022-11-18
  • ISBN : 303121689X
  • Pages : 686 pages

Download or read book Intelligent Systems written by João Carlos Xavier-Junior and published by Springer Nature. This book was released on 2022-11-18 with total page 686 pages. Available in PDF, EPUB and Kindle. Book excerpt: The two-volume set LNAI 13653 and 13654 constitutes the refereed proceedings of the 11th Brazilian Conference on Intelligent Systems, BRACIS 2022, which took place in Campinas, Brazil, in November/December 2022. The 89 papers presented in the proceedings were carefully reviewed and selected from 225 submissions. The conference deals with theoretical aspects and applications of artificial and computational intelligence.

Book Hands On Generative Adversarial Networks with Keras

Download or read book Hands On Generative Adversarial Networks with Keras written by Rafael Valle and published by Packt Publishing Ltd. This book was released on 2019-05-03 with total page 263 pages. Available in PDF, EPUB and Kindle. Book excerpt: Develop generative models for a variety of real-world use-cases and deploy them to production Key FeaturesDiscover various GAN architectures using Python and Keras libraryUnderstand how GAN models function with the help of theoretical and practical examplesApply your learnings to become an active contributor to open source GAN applicationsBook Description Generative Adversarial Networks (GANs) have revolutionized the fields of machine learning and deep learning. This book will be your first step towards understanding GAN architectures and tackling the challenges involved in training them. This book opens with an introduction to deep learning and generative models, and their applications in artificial intelligence (AI). You will then learn how to build, evaluate, and improve your first GAN with the help of easy-to-follow examples. The next few chapters will guide you through training a GAN model to produce and improve high-resolution images. You will also learn how to implement conditional GANs that give you the ability to control characteristics of GAN outputs. You will build on your knowledge further by exploring a new training methodology for progressive growing of GANs. Moving on, you'll gain insights into state-of-the-art models in image synthesis, speech enhancement, and natural language generation using GANs. In addition to this, you'll be able to identify GAN samples with TequilaGAN. By the end of this book, you will be well-versed with the latest advancements in the GAN framework using various examples and datasets, and you will have the skills you need to implement GAN architectures for several tasks and domains, including computer vision, natural language processing (NLP), and audio processing. Foreword by Ting-Chun Wang, Senior Research Scientist, NVIDIA What you will learnLearn how GANs work and the advantages and challenges of working with themControl the output of GANs with the help of conditional GANs, using embedding and space manipulationApply GANs to computer vision, NLP, and audio processingUnderstand how to implement progressive growing of GANsUse GANs for image synthesis and speech enhancementExplore the future of GANs in visual and sonic artsImplement pix2pixHD to turn semantic label maps into photorealistic imagesWho this book is for This book is for machine learning practitioners, deep learning researchers, and AI enthusiasts who are looking for a perfect mix of theory and hands-on content in order to implement GANs using Keras. Working knowledge of Python is expected.

Book Bayesian Tensor Decomposition for Signal Processing and Machine Learning

Download or read book Bayesian Tensor Decomposition for Signal Processing and Machine Learning written by Lei Cheng and published by Springer Nature. This book was released on 2023-02-16 with total page 189 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book presents recent advances of Bayesian inference in structured tensor decompositions. It explains how Bayesian modeling and inference lead to tuning-free tensor decomposition algorithms, which achieve state-of-the-art performances in many applications, including blind source separation; social network mining; image and video processing; array signal processing; and, wireless communications. The book begins with an introduction to the general topics of tensors and Bayesian theories. It then discusses probabilistic models of various structured tensor decompositions and their inference algorithms, with applications tailored for each tensor decomposition presented in the corresponding chapters. The book concludes by looking to the future, and areas where this research can be further developed. Bayesian Tensor Decomposition for Signal Processing and Machine Learning is suitable for postgraduates and researchers with interests in tensor data analytics and Bayesian methods.

Book Advances in Design  Simulation and Manufacturing III

Download or read book Advances in Design Simulation and Manufacturing III written by Vitalii Ivanov and published by Springer Nature. This book was released on 2020-06-04 with total page 588 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book reports on topics at the interface between manufacturing and materials engineering, with a special emphasis on design and simulation issues. Specifically, it covers the development of CAx technologies for product design, the implementation of smart manufacturing systems and Industry 4.0 strategies, topics in technological assurance, numerical simulation and experimental studies on cutting, milling, grinding, pressing and profiling processes, as well as the development and implementation of new advanced materials. Based on the 3rd International Conference on Design, Simulation, Manufacturing: The Innovation Exchange (DSMIE-2020), held on June 9-12, 2020 in Kharkiv, Ukraine, this first volume in a two-volume set provides academics and professionals with extensive information on the latest trends, technologies, challenges and practice-oriented lessons learned in the above-mentioned areas.

Book Machine Intelligence and Smart Systems

Download or read book Machine Intelligence and Smart Systems written by Shikha Agrawal and published by Springer Nature. This book was released on 2022-05-23 with total page 558 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book is a collection of peer-reviewed best selected research papers presented at the Second International Conference on Machine Intelligence and Smart Systems (MISS 2021), organized during September 24–25, 2021, in Gwalior, India. The book presents new advances and research results in the fields of machine intelligence, artificial intelligence and smart systems. It includes main paradigms of machine intelligence algorithms, namely (1) neural networks, (2) evolutionary computation, (3) swarm intelligence, (4) fuzzy systems and (5) immunological computation. Scientists, engineers, academicians, technology developers, researchers, students and government officials will find this book useful in handling their complicated real-world issues by using machine intelligence methodologies.