Cooperative Learning Of Deep Generative Models With Application In Sound Synthesis

Download Cooperative Learning Of Deep Generative Models With Application In Sound Synthesis full books in PDF, epub, and Kindle. Read online Cooperative Learning Of Deep Generative Models With Application In Sound Synthesis ebook anywhere anytime directly on your device. Fast Download speed and no annoying ads. We cannot guarantee that every ebooks is available!

Cooperative Learning of Deep Generative Models with Application in Sound Synthesis

Author : Ruiqi Zhong
Publisher :
ISBN 13 :
Total Pages : 37 pages
Book Rating : 4.:/5 (17 download)

DOWNLOAD NOW!

Book Synopsis Cooperative Learning of Deep Generative Models with Application in Sound Synthesis by : Ruiqi Zhong

Download or read book Cooperative Learning of Deep Generative Models with Application in Sound Synthesis written by Ruiqi Zhong and published by . This book was released on 2017 with total page 37 pages. Available in PDF, EPUB and Kindle. Book excerpt: Fires, rainstorms or insect swarms produce natural sounds made up of rapidly occurring acoustic events. which we call "sound textures". This kind of phenomena have been studied by computational audio community [MS11] and neural science people for a long time. From previous studies, it has been verified that sound textures can be schematically synthesized from statistical models fairly well. Here we take a novel approach involving neural networks or deep learning methods. Specifically, we use cooperative training of a descriptor and a generator network, modeled as a convolutional neural network(ConvNet) and a deconvolu- tional neural network(DeconvNet) respectively. From several experiments, we proved that our framework can capture the essence of sound textures and synthesize identifiable natural sound

Deep Generative Models, and Data Augmentation, Labelling, and Imperfections

Author : Sandy Engelhardt
Publisher : Springer Nature
ISBN 13 : 3030882101
Total Pages : 278 pages
Book Rating : 4.0/5 (38 download)

DOWNLOAD NOW!

Book Synopsis Deep Generative Models, and Data Augmentation, Labelling, and Imperfections by : Sandy Engelhardt

Download or read book Deep Generative Models, and Data Augmentation, Labelling, and Imperfections written by Sandy Engelhardt and published by Springer Nature. This book was released on 2021-09-29 with total page 278 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the refereed proceedings of the First MICCAI Workshop on Deep Generative Models, DG4MICCAI 2021, and the First MICCAI Workshop on Data Augmentation, Labelling, and Imperfections, DALI 2021, held in conjunction with MICCAI 2021, in October 2021. The workshops were planned to take place in Strasbourg, France, but were held virtually due to the COVID-19 pandemic. DG4MICCAI 2021 accepted 12 papers from the 17 submissions received. The workshop focusses on recent algorithmic developments, new results, and promising future directions in Deep Generative Models. Deep generative models such as Generative Adversarial Network (GAN) and Variational Auto-Encoder (VAE) are currently receiving widespread attention from not only the computer vision and machine learning communities, but also in the MIC and CAI community. For DALI 2021, 15 papers from 32 submissions were accepted for publication. They focus on rigorous study of medical data related to machine learning systems.

Computer Vision – ECCV 2022

Author : Shai Avidan
Publisher : Springer Nature
ISBN 13 : 3031198360
Total Pages : 808 pages
Book Rating : 4.0/5 (311 download)

DOWNLOAD NOW!

Book Synopsis Computer Vision – ECCV 2022 by : Shai Avidan

Download or read book Computer Vision – ECCV 2022 written by Shai Avidan and published by Springer Nature. This book was released on 2022-10-22 with total page 808 pages. Available in PDF, EPUB and Kindle. Book excerpt: The 39-volume set, comprising the LNCS books 13661 until 13699, constitutes the refereed proceedings of the 17th European Conference on Computer Vision, ECCV 2022, held in Tel Aviv, Israel, during October 23–27, 2022. The 1645 papers presented in these proceedings were carefully reviewed and selected from a total of 5804 submissions. The papers deal with topics such as computer vision; machine learning; deep neural networks; reinforcement learning; object recognition; image classification; image processing; object detection; semantic segmentation; human pose estimation; 3d reconstruction; stereo vision; computational photography; neural networks; image coding; image reconstruction; object recognition; motion estimation.

Distributed Strategic Learning for Wireless Engineers

Author : Hamidou Tembine
Publisher : CRC Press
ISBN 13 : 1439876371
Total Pages : 498 pages
Book Rating : 4.4/5 (398 download)

DOWNLOAD NOW!

Book Synopsis Distributed Strategic Learning for Wireless Engineers by : Hamidou Tembine

Download or read book Distributed Strategic Learning for Wireless Engineers written by Hamidou Tembine and published by CRC Press. This book was released on 2012-05-18 with total page 498 pages. Available in PDF, EPUB and Kindle. Book excerpt: Although valued for its ability to allow teams to collaborate and foster coalitional behaviors among the participants, game theory’s application to networking systems is not without challenges. Distributed Strategic Learning for Wireless Engineers illuminates the promise of learning in dynamic games as a tool for analyzing network evolution and underlines the potential pitfalls and difficulties likely to be encountered. Establishing the link between several theories, this book demonstrates what is needed to learn strategic interaction in wireless networks under uncertainty, randomness, and time delays. It addresses questions such as: How much information is enough for effective distributed decision making? Is having more information always useful in terms of system performance? What are the individual learning performance bounds under outdated and imperfect measurement? What are the possible dynamics and outcomes if the players adopt different learning patterns? If convergence occurs, what is the convergence time of heterogeneous learning? What are the issues of hybrid learning? How can one develop fast and efficient learning schemes in scenarios where some players have more information than the others? What is the impact of risk-sensitivity in strategic learning systems? How can one construct learning schemes in a dynamic environment in which one of the players do not observe a numerical value of its own-payoffs but only a signal of it? How can one learn "unstable" equilibria and global optima in a fully distributed manner? The book provides an explicit description of how players attempt to learn over time about the game and about the behavior of others. It focuses on finite and infinite systems, where the interplay among the individual adjustments undertaken by the different players generates different learning dynamics, heterogeneous learning, risk-sensitive learning, and hybrid dynamics.

Deep Learning

Author : Li Deng
Publisher :
ISBN 13 : 9781601988140
Total Pages : 212 pages
Book Rating : 4.9/5 (881 download)

DOWNLOAD NOW!

Book Synopsis Deep Learning by : Li Deng

Download or read book Deep Learning written by Li Deng and published by . This book was released on 2014 with total page 212 pages. Available in PDF, EPUB and Kindle. Book excerpt: Provides an overview of general deep learning methodology and its applications to a variety of signal and information processing tasks

INSIDE GENERATIVE AI

Author : Rick Spair
Publisher : Rick Spair
ISBN 13 :
Total Pages : 146 pages
Book Rating : 4./5 ( download)

DOWNLOAD NOW!

Book Synopsis INSIDE GENERATIVE AI by : Rick Spair

Download or read book INSIDE GENERATIVE AI written by Rick Spair and published by Rick Spair. This book was released on with total page 146 pages. Available in PDF, EPUB and Kindle. Book excerpt: Generative AI represents a groundbreaking frontier in the realm of artificial intelligence, where machines not only learn from data but also create new data, mimicking the inventive processes of human creativity. This book is a comprehensive guide that explores the depths of generative AI, from foundational concepts to advanced applications, and provides a rich array of hands-on projects and real-world case studies. Why Generative AI? In recent years, generative AI has transformed from a niche area of research to a central pillar of AI innovation, with profound implications for various industries. From generating realistic images and videos to composing music and writing compelling narratives, generative AI models are pushing the boundaries of what machines can do. This evolution has not only expanded the capabilities of AI but also sparked new forms of creative expression and problem-solving. Generative AI's impact is evident in numerous fields: Art and Design: Artists and designers are leveraging AI to create stunning visual artworks, intricate designs, and immersive digital environments. Tools like DeepDream and GauGAN have opened new horizons in artistic creativity, enabling the generation of unique and surreal visuals. Media and Entertainment: The media industry is using generative AI to automate content creation, from news articles to movie scripts, and even to generate entire virtual worlds for video games and virtual reality experiences. AI-generated music and soundtracks are also becoming increasingly popular, offering new ways to enhance auditory experiences. Healthcare: In healthcare, generative AI is aiding in the discovery of new drugs, personalizing treatment plans, and enhancing medical imaging. By generating realistic simulations and models, AI helps researchers and practitioners explore new avenues in medical science. Business and Marketing: Businesses are employing generative AI to create personalized marketing content, design products, and optimize supply chains. AI-driven tools are enabling companies to innovate faster and more efficiently, providing a competitive edge in the market. Dive into the projects, experiment with different models, and engage with the AI community. By learning, creating, and sharing, you become a part of the vibrant and dynamic landscape of generative AI. The future is filled with opportunities, and this book is your gateway to exploring and contributing to the exciting world of generative AI. Welcome to the journey!

Deep Learning Techniques for Music Generation

Author : Jean-Pierre Briot
Publisher : Springer
ISBN 13 : 3319701630
Total Pages : 284 pages
Book Rating : 4.3/5 (197 download)

DOWNLOAD NOW!

Book Synopsis Deep Learning Techniques for Music Generation by : Jean-Pierre Briot

Download or read book Deep Learning Techniques for Music Generation written by Jean-Pierre Briot and published by Springer. This book was released on 2019-11-08 with total page 284 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book is a survey and analysis of how deep learning can be used to generate musical content. The authors offer a comprehensive presentation of the foundations of deep learning techniques for music generation. They also develop a conceptual framework used to classify and analyze various types of architecture, encoding models, generation strategies, and ways to control the generation. The five dimensions of this framework are: objective (the kind of musical content to be generated, e.g., melody, accompaniment); representation (the musical elements to be considered and how to encode them, e.g., chord, silence, piano roll, one-hot encoding); architecture (the structure organizing neurons, their connexions, and the flow of their activations, e.g., feedforward, recurrent, variational autoencoder); challenge (the desired properties and issues, e.g., variability, incrementality, adaptability); and strategy (the way to model and control the process of generation, e.g., single-step feedforward, iterative feedforward, decoder feedforward, sampling). To illustrate the possible design decisions and to allow comparison and correlation analysis they analyze and classify more than 40 systems, and they discuss important open challenges such as interactivity, originality, and structure. The authors have extensive knowledge and experience in all related research, technical, performance, and business aspects. The book is suitable for students, practitioners, and researchers in the artificial intelligence, machine learning, and music creation domains. The reader does not require any prior knowledge about artificial neural networks, deep learning, or computer music. The text is fully supported with a comprehensive table of acronyms, bibliography, glossary, and index, and supplementary material is available from the authors' website.

Dive Into Deep Learning

Author : Joanne Quinn
Publisher : Corwin Press
ISBN 13 : 1544385404
Total Pages : 297 pages
Book Rating : 4.5/5 (443 download)

DOWNLOAD NOW!

Book Synopsis Dive Into Deep Learning by : Joanne Quinn

Download or read book Dive Into Deep Learning written by Joanne Quinn and published by Corwin Press. This book was released on 2019-07-15 with total page 297 pages. Available in PDF, EPUB and Kindle. Book excerpt: The leading experts in system change and learning, with their school-based partners around the world, have created this essential companion to their runaway best-seller, Deep Learning: Engage the World Change the World. This hands-on guide provides a roadmap for building capacity in teachers, schools, districts, and systems to design deep learning, measure progress, and assess conditions needed to activate and sustain innovation. Dive Into Deep Learning: Tools for Engagement is rich with resources educators need to construct and drive meaningful deep learning experiences in order to develop the kind of mindset and know-how that is crucial to becoming a problem-solving change agent in our global society. Designed in full color, this easy-to-use guide is loaded with tools, tips, protocols, and real-world examples. It includes: • A framework for deep learning that provides a pathway to develop the six global competencies needed to flourish in a complex world — character, citizenship, collaboration, communication, creativity, and critical thinking. • Learning progressions to help educators analyze student work and measure progress. • Learning design rubrics, templates and examples for incorporating the four elements of learning design: learning partnerships, pedagogical practices, learning environments, and leveraging digital. • Conditions rubrics, teacher self-assessment tools, and planning guides to help educators build, mobilize, and sustain deep learning in schools and districts. Learn about, improve, and expand your world of learning. Put the joy back into learning for students and adults alike. Dive into deep learning to create learning experiences that give purpose, unleash student potential, and transform not only learning, but life itself.

Deep Learning

Author : Ian Goodfellow
Publisher : MIT Press
ISBN 13 : 0262337371
Total Pages : 801 pages
Book Rating : 4.2/5 (623 download)

DOWNLOAD NOW!

Book Synopsis Deep Learning by : Ian Goodfellow

Download or read book Deep Learning written by Ian Goodfellow and published by MIT Press. This book was released on 2016-11-10 with total page 801 pages. Available in PDF, EPUB and Kindle. Book excerpt: An introduction to a broad range of topics in deep learning, covering mathematical and conceptual background, deep learning techniques used in industry, and research perspectives. “Written by three experts in the field, Deep Learning is the only comprehensive book on the subject.” —Elon Musk, cochair of OpenAI; cofounder and CEO of Tesla and SpaceX Deep learning is a form of machine learning that enables computers to learn from experience and understand the world in terms of a hierarchy of concepts. Because the computer gathers knowledge from experience, there is no need for a human computer operator to formally specify all the knowledge that the computer needs. The hierarchy of concepts allows the computer to learn complicated concepts by building them out of simpler ones; a graph of these hierarchies would be many layers deep. This book introduces a broad range of topics in deep learning. The text offers mathematical and conceptual background, covering relevant concepts in linear algebra, probability theory and information theory, numerical computation, and machine learning. It describes deep learning techniques used by practitioners in industry, including deep feedforward networks, regularization, optimization algorithms, convolutional networks, sequence modeling, and practical methodology; and it surveys such applications as natural language processing, speech recognition, computer vision, online recommendation systems, bioinformatics, and videogames. Finally, the book offers research perspectives, covering such theoretical topics as linear factor models, autoencoders, representation learning, structured probabilistic models, Monte Carlo methods, the partition function, approximate inference, and deep generative models. Deep Learning can be used by undergraduate or graduate students planning careers in either industry or research, and by software engineers who want to begin using deep learning in their products or platforms. A website offers supplementary material for both readers and instructors.

Spoken Language Understanding

Author : Gokhan Tur
Publisher : John Wiley & Sons
ISBN 13 : 1119993946
Total Pages : 443 pages
Book Rating : 4.1/5 (199 download)

DOWNLOAD NOW!

Book Synopsis Spoken Language Understanding by : Gokhan Tur

Download or read book Spoken Language Understanding written by Gokhan Tur and published by John Wiley & Sons. This book was released on 2011-05-03 with total page 443 pages. Available in PDF, EPUB and Kindle. Book excerpt: Spoken language understanding (SLU) is an emerging field in between speech and language processing, investigating human/ machine and human/ human communication by leveraging technologies from signal processing, pattern recognition, machine learning and artificial intelligence. SLU systems are designed to extract the meaning from speech utterances and its applications are vast, from voice search in mobile devices to meeting summarization, attracting interest from both commercial and academic sectors. Both human/machine and human/human communications can benefit from the application of SLU, using differing tasks and approaches to better understand and utilize such communications. This book covers the state-of-the-art approaches for the most popular SLU tasks with chapters written by well-known researchers in the respective fields. Key features include: Presents a fully integrated view of the two distinct disciplines of speech processing and language processing for SLU tasks. Defines what is possible today for SLU as an enabling technology for enterprise (e.g., customer care centers or company meetings), and consumer (e.g., entertainment, mobile, car, robot, or smart environments) applications and outlines the key research areas. Provides a unique source of distilled information on methods for computer modeling of semantic information in human/machine and human/human conversations. This book can be successfully used for graduate courses in electronics engineering, computer science or computational linguistics. Moreover, technologists interested in processing spoken communications will find it a useful source of collated information of the topic drawn from the two distinct disciplines of speech processing and language processing under the new area of SLU.

How Learning Works

Author : Susan A. Ambrose
Publisher : John Wiley & Sons
ISBN 13 : 0470617608
Total Pages : 336 pages
Book Rating : 4.4/5 (76 download)

DOWNLOAD NOW!

Book Synopsis How Learning Works by : Susan A. Ambrose

Download or read book How Learning Works written by Susan A. Ambrose and published by John Wiley & Sons. This book was released on 2010-04-16 with total page 336 pages. Available in PDF, EPUB and Kindle. Book excerpt: Praise for How Learning Works "How Learning Works is the perfect title for this excellent book. Drawing upon new research in psychology, education, and cognitive science, the authors have demystified a complex topic into clear explanations of seven powerful learning principles. Full of great ideas and practical suggestions, all based on solid research evidence, this book is essential reading for instructors at all levels who wish to improve their students' learning." —Barbara Gross Davis, assistant vice chancellor for educational development, University of California, Berkeley, and author, Tools for Teaching "This book is a must-read for every instructor, new or experienced. Although I have been teaching for almost thirty years, as I read this book I found myself resonating with many of its ideas, and I discovered new ways of thinking about teaching." —Eugenia T. Paulus, professor of chemistry, North Hennepin Community College, and 2008 U.S. Community Colleges Professor of the Year from The Carnegie Foundation for the Advancement of Teaching and the Council for Advancement and Support of Education "Thank you Carnegie Mellon for making accessible what has previously been inaccessible to those of us who are not learning scientists. Your focus on the essence of learning combined with concrete examples of the daily challenges of teaching and clear tactical strategies for faculty to consider is a welcome work. I will recommend this book to all my colleagues." —Catherine M. Casserly, senior partner, The Carnegie Foundation for the Advancement of Teaching "As you read about each of the seven basic learning principles in this book, you will find advice that is grounded in learning theory, based on research evidence, relevant to college teaching, and easy to understand. The authors have extensive knowledge and experience in applying the science of learning to college teaching, and they graciously share it with you in this organized and readable book." —From the Foreword by Richard E. Mayer, professor of psychology, University of California, Santa Barbara; coauthor, e-Learning and the Science of Instruction; and author, Multimedia Learning

Cooperative/Collaborative Learning

Author : Robyn M. Gillies
Publisher : Mdpi AG
ISBN 13 : 9783036529714
Total Pages : 220 pages
Book Rating : 4.5/5 (297 download)

DOWNLOAD NOW!

Book Synopsis Cooperative/Collaborative Learning by : Robyn M. Gillies

Download or read book Cooperative/Collaborative Learning written by Robyn M. Gillies and published by Mdpi AG. This book was released on 2022-01-26 with total page 220 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book brings together a diverse range of international scholars to highlight recent developments in research on collaborative learning. The emphasis is on research that has a strong evidence base for the work that is presented and includes empirical studies, best evidence synthesis of the relevant research, case studies, and theoretical reports. It also highlights how different technologies have been used to facilitate group interaction, dialogue, and learning. There is much to be gained by sharing and learning about what happens in different disciplines and contexts and how different collaborative pedagogies can be implemented when needed to promote understanding and learning. This book will have strong appeal to pre-service and experienced teachers and researchers who are interested in how different collaborative pedagogies can be embedded in course curricula to promote student engagement and learning.

Speech Enhancement

Author : Shoji Makino
Publisher : Springer Science & Business Media
ISBN 13 : 9783540240396
Total Pages : 432 pages
Book Rating : 4.2/5 (43 download)

DOWNLOAD NOW!

Book Synopsis Speech Enhancement by : Shoji Makino

Download or read book Speech Enhancement written by Shoji Makino and published by Springer Science & Business Media. This book was released on 2005-03-17 with total page 432 pages. Available in PDF, EPUB and Kindle. Book excerpt: We live in a noisy world! In all applications (telecommunications, hands-free communications, recording, human-machine interfaces, etc) that require at least one microphone, the signal of interest is usually contaminated by noise and reverberation. As a result, the microphone signal has to be "cleaned" with digital signal processing tools before it is played out, transmitted, or stored. This book is about speech enhancement. Different well-known and state-of-the-art methods for noise reduction, with one or multiple microphones, are discussed. By speech enhancement, we mean not only noise reduction but also dereverberation and separation of independent signals. These topics are also covered in this book. However, the general emphasis is on noise reduction because of the large number of applications that can benefit from this technology. The goal of this book is to provide a strong reference for researchers, engineers, and graduate students who are interested in the problem of signal and speech enhancement. To do so, we invited well-known experts to contribute chapters covering the state of the art in this focused field.

Artificial Intelligence in Healthcare

Author : Adam Bohr
Publisher : Academic Press
ISBN 13 : 0128184396
Total Pages : 385 pages
Book Rating : 4.1/5 (281 download)

DOWNLOAD NOW!

Book Synopsis Artificial Intelligence in Healthcare by : Adam Bohr

Download or read book Artificial Intelligence in Healthcare written by Adam Bohr and published by Academic Press. This book was released on 2020-06-21 with total page 385 pages. Available in PDF, EPUB and Kindle. Book excerpt: Artificial Intelligence (AI) in Healthcare is more than a comprehensive introduction to artificial intelligence as a tool in the generation and analysis of healthcare data. The book is split into two sections where the first section describes the current healthcare challenges and the rise of AI in this arena. The ten following chapters are written by specialists in each area, covering the whole healthcare ecosystem. First, the AI applications in drug design and drug development are presented followed by its applications in the field of cancer diagnostics, treatment and medical imaging. Subsequently, the application of AI in medical devices and surgery are covered as well as remote patient monitoring. Finally, the book dives into the topics of security, privacy, information sharing, health insurances and legal aspects of AI in healthcare. - Highlights different data techniques in healthcare data analysis, including machine learning and data mining - Illustrates different applications and challenges across the design, implementation and management of intelligent systems and healthcare data networks - Includes applications and case studies across all areas of AI in healthcare data

Education for Life and Work

Author : National Research Council
Publisher : National Academies Press
ISBN 13 : 0309256496
Total Pages : 203 pages
Book Rating : 4.3/5 (92 download)

DOWNLOAD NOW!

Book Synopsis Education for Life and Work by : National Research Council

Download or read book Education for Life and Work written by National Research Council and published by National Academies Press. This book was released on 2013-01-18 with total page 203 pages. Available in PDF, EPUB and Kindle. Book excerpt: Americans have long recognized that investments in public education contribute to the common good, enhancing national prosperity and supporting stable families, neighborhoods, and communities. Education is even more critical today, in the face of economic, environmental, and social challenges. Today's children can meet future challenges if their schooling and informal learning activities prepare them for adult roles as citizens, employees, managers, parents, volunteers, and entrepreneurs. To achieve their full potential as adults, young people need to develop a range of skills and knowledge that facilitate mastery and application of English, mathematics, and other school subjects. At the same time, business and political leaders are increasingly asking schools to develop skills such as problem solving, critical thinking, communication, collaboration, and self-management - often referred to as "21st century skills." Education for Life and Work: Developing Transferable Knowledge and Skills in the 21st Century describes this important set of key skills that increase deeper learning, college and career readiness, student-centered learning, and higher order thinking. These labels include both cognitive and non-cognitive skills- such as critical thinking, problem solving, collaboration, effective communication, motivation, persistence, and learning to learn. 21st century skills also include creativity, innovation, and ethics that are important to later success and may be developed in formal or informal learning environments. This report also describes how these skills relate to each other and to more traditional academic skills and content in the key disciplines of reading, mathematics, and science. Education for Life and Work: Developing Transferable Knowledge and Skills in the 21st Century summarizes the findings of the research that investigates the importance of such skills to success in education, work, and other areas of adult responsibility and that demonstrates the importance of developing these skills in K-16 education. In this report, features related to learning these skills are identified, which include teacher professional development, curriculum, assessment, after-school and out-of-school programs, and informal learning centers such as exhibits and museums.

Synthetic Data for Deep Learning

Author : Sergey I. Nikolenko
Publisher : Springer Nature
ISBN 13 : 3030751783
Total Pages : 348 pages
Book Rating : 4.0/5 (37 download)

DOWNLOAD NOW!

Book Synopsis Synthetic Data for Deep Learning by : Sergey I. Nikolenko

Download or read book Synthetic Data for Deep Learning written by Sergey I. Nikolenko and published by Springer Nature. This book was released on 2021-06-26 with total page 348 pages. Available in PDF, EPUB and Kindle. Book excerpt: This is the first book on synthetic data for deep learning, and its breadth of coverage may render this book as the default reference on synthetic data for years to come. The book can also serve as an introduction to several other important subfields of machine learning that are seldom touched upon in other books. Machine learning as a discipline would not be possible without the inner workings of optimization at hand. The book includes the necessary sinews of optimization though the crux of the discussion centers on the increasingly popular tool for training deep learning models, namely synthetic data. It is expected that the field of synthetic data will undergo exponential growth in the near future. This book serves as a comprehensive survey of the field. In the simplest case, synthetic data refers to computer-generated graphics used to train computer vision models. There are many more facets of synthetic data to consider. In the section on basic computer vision, the book discusses fundamental computer vision problems, both low-level (e.g., optical flow estimation) and high-level (e.g., object detection and semantic segmentation), synthetic environments and datasets for outdoor and urban scenes (autonomous driving), indoor scenes (indoor navigation), aerial navigation, and simulation environments for robotics. Additionally, it touches upon applications of synthetic data outside computer vision (in neural programming, bioinformatics, NLP, and more). It also surveys the work on improving synthetic data development and alternative ways to produce it such as GANs. The book introduces and reviews several different approaches to synthetic data in various domains of machine learning, most notably the following fields: domain adaptation for making synthetic data more realistic and/or adapting the models to be trained on synthetic data and differential privacy for generating synthetic data with privacy guarantees. This discussion is accompanied by an introduction into generative adversarial networks (GAN) and an introduction to differential privacy.

Intelligent Music Production

Author : Brecht De Man
Publisher : Routledge
ISBN 13 : 1351679023
Total Pages : 435 pages
Book Rating : 4.3/5 (516 download)

DOWNLOAD NOW!

Book Synopsis Intelligent Music Production by : Brecht De Man

Download or read book Intelligent Music Production written by Brecht De Man and published by Routledge. This book was released on 2019-11-07 with total page 435 pages. Available in PDF, EPUB and Kindle. Book excerpt: Intelligent Music Production presents the state of the art in approaches, methodologies and systems from the emerging field of automation in music mixing and mastering. This book collects the relevant works in the domain of innovation in music production, and orders them in a way that outlines the way forward: first, covering our knowledge of the music production processes; then by reviewing the methodologies in classification, data collection and perceptual evaluation; and finally by presenting recent advances on introducing intelligence in audio effects, sound engineering processes and music production interfaces. Intelligent Music Production is a comprehensive guide, providing an introductory read for beginners, as well as a crucial reference point for experienced researchers, producers, engineers and developers.