Machine learning paradigms [Documento eletrónico] : advances in deep learning-based technological applications / edited by George A. Tsihrintzis, Lakhmi C. Jain
Language: eng.Country: Switzerland, Swiss Confederation, Cham.Publication: Cham : Springer International Publishing, 2020Description: XII, 430 p. : il.ISBN: 978-3-030-49724-8.Series: Learning and Analytics in Intelligent Systems, vol. 18Subject - Topical Name: Machine learning | Ciência computacional Online Resources:Click here to access onlineItem type | Current library | Collection | Call number | Copy number | Status | Date due | Barcode | |
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E-Books | Biblioteca NOVA FCT Online | Não Ficção | Q325.5.SPR FCT 103661 (Browse shelf(Opens below)) | 1 | Available | 96374 |
At 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.
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