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OverviewAt the dawn of the 4th Industrial Revolution, the field of Deep Learning (a sub-field of Artificial Intelligence and Machine Learning) is growing continuously and rapidly, developing both theoretically and towards applications in increasingly many and diverse other disciplines. The book at hand aims at exposing its reader to some of the most significant recent advances in deep learning-based technological applications and consists of an editorial note and an additional fifteen (15) chapters. All chapters in the book were invited from authors who work in the corresponding chapter theme and are recognized for their significant research contributions. In more detail, the chapters in the book are organized into six parts, namely (1) Deep Learning in Sensing, (2) Deep Learning in Social Media and IOT, (3) Deep Learning in the Medical Field, (4) Deep Learning in Systems Control, (5) Deep Learning in Feature Vector Processing, and (6) Evaluation of Algorithm Performance. This research book is directed towards professors, researchers, scientists, engineers and students in computer science-related disciplines. It is also directed towards readers who come from other disciplines and are interested in becoming versed in some of the most recent deep learning-based technological applications. An extensive list of bibliographic references at the end of each chapter guides the readers to probe deeper into their application areas of interest. Full Product DetailsAuthor: George A. Tsihrintzis , Lakhmi C. JainPublisher: Springer Nature Switzerland AG Imprint: Springer Nature Switzerland AG Edition: 1st ed. 2020 Volume: 18 Weight: 0.676kg ISBN: 9783030497262ISBN 10: 3030497267 Pages: 430 Publication Date: 25 July 2021 Audience: Professional and scholarly , Professional & Vocational Format: Paperback Publisher's Status: Active Availability: Manufactured on demand  We will order this item for you from a manufactured on demand supplier. Table of ContentsChapter 1: Introduction to Deep Learning-based Technological Applications.- Chapter 2: Vision to Language: Methods, Metrics and Datasets.- Chapter 3: Deep Learning Techniques for Geospatial Data Analysis.- Chapter 4: Deep Learning Approaches in Food Recognition.- Chapter 5: Deep Learning for Twitter Sentiment Analysis: the Effect of pre-trained Word Embedding.- Chapter 6: A Good Defense is a Strong DNN: Defending the IoT with Deep Neural Networks.- Chapter 7: Survey on Deep Learning Techniques for Medical Imaging Application Area.- Chapter 8: Deep Learning Methods in Electroencephalography.Reviews“A very important and truly outstanding Contribution … . I recommend it as a ‘must read’ reference for researchers, practitioners, and higher research degrees students who want to experience truly exciting deep dive into a full-fledged deep learning. … the most important advantage of the book is the fact that it leaves its reader with a heightened ability to think – in different ways – about developing, evaluating, and implementing deep learning-based techniques and technologies in real life environments.” (Edward Szczerbicki, Intelligent Decision Technologies, Vol. 15, 2021) A very important and truly outstanding Contribution ... . I recommend it as a 'must read' reference for researchers, practitioners, and higher research degrees students who want to experience truly exciting deep dive into a full-fledged deep learning. ... the most important advantage of the book is the fact that it leaves its reader with a heightened ability to think - in different ways - about developing, evaluating, and implementing deep learning-based techniques and technologies in real life environments. (Edward Szczerbicki, Intelligent Decision Technologies, Vol. 15, 2021) Author InformationTab Content 6Author Website:Countries AvailableAll regions |
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