Machine Learning Paradigms
Advances in Deep Learning-based Technological Applications
(Sprache: Englisch)
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...
Voraussichtlich lieferbar in 3 Tag(en)
versandkostenfrei
Buch (Kartoniert)
164.99 €
- Lastschrift, Kreditkarte, Paypal, Rechnung
- Kostenlose Rücksendung
- Ratenzahlung möglich
Produktdetails
Produktinformationen zu „Machine Learning Paradigms “
Klappentext zu „Machine Learning Paradigms “
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.
Inhaltsverzeichnis zu „Machine Learning Paradigms “
Chapter 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.
Bibliographische Angaben
- 2021, 1st ed. 2020, XII, 430 Seiten, 154 farbige Abbildungen, Maße: 15,5 x 23,5 cm, Kartoniert (TB), Englisch
- Herausgegeben: George A Tsihrintzis, Lakhmi C Jain
- Verlag: Springer, Berlin
- ISBN-10: 3030497267
- ISBN-13: 9783030497262
Sprache:
Englisch
Pressezitat
"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)
Kommentar zu "Machine Learning Paradigms"
Schreiben Sie einen Kommentar zu "Machine Learning Paradigms".
Kommentar verfassen