Deep learning techniques for automation and industrial applications:
This book provides state-of-the-art approaches to deep learning in areas of detection and prediction, as well as future framework development, building service systems and analytical aspects in which artificial neural networks, fuzzy logic, genetic algorithms, and hybrid mechanisms are used. Deep le...
Gespeichert in:
| Weitere beteiligte Personen: | , , , , , |
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| Format: | Elektronisch E-Book |
| Sprache: | Englisch |
| Veröffentlicht: |
Hoboken, NJ Beverly, MA
John Wiley & Sons, Inc.
2024
Hoboken, NJ Beverly, MA Scrivener Publishing LLC 2024 |
| Schlagwörter: | |
| Links: | https://learning.oreilly.com/library/view/-/9781394234240/?ar |
| Zusammenfassung: | This book provides state-of-the-art approaches to deep learning in areas of detection and prediction, as well as future framework development, building service systems and analytical aspects in which artificial neural networks, fuzzy logic, genetic algorithms, and hybrid mechanisms are used. Deep learning algorithms and techniques are found to be useful in various areas, such as automatic machine translation, automatic handwriting generation, visual recognition, fraud detection, and detecting developmental delays in children. "Deep Learning Techniques for Automation and Industrial Applications" presents a concise introduction to the recent advances in this field of artificial intelligence (AI). The broad-ranging discussion covers the algorithms and applications in AI, reasoning, machine learning, neural networks, reinforcement learning, and their applications in various domains like agriculture, manufacturing, and healthcare. Applying deep learning techniques or algorithms successfully in these areas requires a concerted effort, fostering integrative research between experts from diverse disciplines from data science to visualization. This book provides state-of-the-art approaches to deep learning covering detection and prediction, as well as future framework development, building service systems, and analytical aspects. For all these topics, various approaches to deep learning, such as artificial neural networks, fuzzy logic, genetic algorithms, and hybrid mechanisms, are explained. Audience The book will be useful to researchers and industry engineers working in information technology, data analytics network security, and manufacturing. Graduate and upper-level undergraduate students in advanced modeling and simulation courses will find this book very useful. |
| Beschreibung: | Description based upon print version of record. - 6.4 Results and Discussions. - Description based on online resource; title from digital title page (viewed on June 26, 2024) |
| Umfang: | 1 Online-Ressource (280 Seiten) |
| ISBN: | 9781394234271 1394234279 9781394234264 1394234260 9781394234240 |
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| 520 | |a This book provides state-of-the-art approaches to deep learning in areas of detection and prediction, as well as future framework development, building service systems and analytical aspects in which artificial neural networks, fuzzy logic, genetic algorithms, and hybrid mechanisms are used. Deep learning algorithms and techniques are found to be useful in various areas, such as automatic machine translation, automatic handwriting generation, visual recognition, fraud detection, and detecting developmental delays in children. "Deep Learning Techniques for Automation and Industrial Applications" presents a concise introduction to the recent advances in this field of artificial intelligence (AI). The broad-ranging discussion covers the algorithms and applications in AI, reasoning, machine learning, neural networks, reinforcement learning, and their applications in various domains like agriculture, manufacturing, and healthcare. Applying deep learning techniques or algorithms successfully in these areas requires a concerted effort, fostering integrative research between experts from diverse disciplines from data science to visualization. This book provides state-of-the-art approaches to deep learning covering detection and prediction, as well as future framework development, building service systems, and analytical aspects. For all these topics, various approaches to deep learning, such as artificial neural networks, fuzzy logic, genetic algorithms, and hybrid mechanisms, are explained. Audience The book will be useful to researchers and industry engineers working in information technology, data analytics network security, and manufacturing. Graduate and upper-level undergraduate students in advanced modeling and simulation courses will find this book very useful. | ||
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| 650 | 4 | |a Automatisation | |
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| id | ZDB-30-ORH-106391623 |
| illustrated | Not Illustrated |
| indexdate | 2025-01-17T11:22:11Z |
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| isbn | 9781394234271 1394234279 9781394234264 1394234260 9781394234240 |
| language | English |
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| publishDate | 2024 |
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| publisher | John Wiley & Sons, Inc. Scrivener Publishing LLC |
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| spelling | Deep learning techniques for automation and industrial applications edited by Pramod Singh Rathore... [and 5 others] Hoboken, NJ Beverly, MA John Wiley & Sons, Inc. 2024 Hoboken, NJ Beverly, MA Scrivener Publishing LLC 2024 ©2024 1 Online-Ressource (280 Seiten) Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Description based upon print version of record. - 6.4 Results and Discussions. - Description based on online resource; title from digital title page (viewed on June 26, 2024) This book provides state-of-the-art approaches to deep learning in areas of detection and prediction, as well as future framework development, building service systems and analytical aspects in which artificial neural networks, fuzzy logic, genetic algorithms, and hybrid mechanisms are used. Deep learning algorithms and techniques are found to be useful in various areas, such as automatic machine translation, automatic handwriting generation, visual recognition, fraud detection, and detecting developmental delays in children. "Deep Learning Techniques for Automation and Industrial Applications" presents a concise introduction to the recent advances in this field of artificial intelligence (AI). The broad-ranging discussion covers the algorithms and applications in AI, reasoning, machine learning, neural networks, reinforcement learning, and their applications in various domains like agriculture, manufacturing, and healthcare. Applying deep learning techniques or algorithms successfully in these areas requires a concerted effort, fostering integrative research between experts from diverse disciplines from data science to visualization. This book provides state-of-the-art approaches to deep learning covering detection and prediction, as well as future framework development, building service systems, and analytical aspects. For all these topics, various approaches to deep learning, such as artificial neural networks, fuzzy logic, genetic algorithms, and hybrid mechanisms, are explained. Audience The book will be useful to researchers and industry engineers working in information technology, data analytics network security, and manufacturing. Graduate and upper-level undergraduate students in advanced modeling and simulation courses will find this book very useful. Automation Automatisation automation Rathore, Pramod Singh 1988- HerausgeberIn edt Ahuja, Sachin MitwirkendeR ctb Burri, Srinivasa Rao MitwirkendeR ctb Khunteta, Ajay MitwirkendeR ctb Baliyan, Anupam MitwirkendeR ctb Kumar, Abhishek MitwirkendeR ctb 9781394234240 Erscheint auch als Druck-Ausgabe 9781394234240 |
| spellingShingle | Deep learning techniques for automation and industrial applications Automation Automatisation automation |
| title | Deep learning techniques for automation and industrial applications |
| title_auth | Deep learning techniques for automation and industrial applications |
| title_exact_search | Deep learning techniques for automation and industrial applications |
| title_full | Deep learning techniques for automation and industrial applications edited by Pramod Singh Rathore... [and 5 others] |
| title_fullStr | Deep learning techniques for automation and industrial applications edited by Pramod Singh Rathore... [and 5 others] |
| title_full_unstemmed | Deep learning techniques for automation and industrial applications edited by Pramod Singh Rathore... [and 5 others] |
| title_short | Deep learning techniques for automation and industrial applications |
| title_sort | deep learning techniques for automation and industrial applications |
| topic | Automation Automatisation automation |
| topic_facet | Automation Automatisation automation |
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