Challenges and Opportunities for Deep Learning Applications in Industry 4.0

Vaishali Mehta, Dolly Sharma, Monika Mangla, Anita Gehlot, Rajesh Singh, Sergio Márquez Sánchez

ISBN 10: 9815036084 / ISBN 13: 9789815036084

Published by Bentham Science Publishers, 2022

About this Item

Seller Inventory # LU-9789815036084

Bibliographic Details

• Title: Challenges and Opportunities for Deep Learning Applications in Industry 4.0
• Publisher: Bentham Science Publishers
• Publication Date: 2022
• Language: English
• ISBN 10: 9815036084
• ISBN 13: 9789815036084
• Binding: Paperback
• Condition: New
• Dimensions: 17.78W x 1.37H x 25.4D centimeters 17.78 centimeters width by 1.37 centimeters height by 25.4 centimeters depth
• Weight: 558 grams

About this title

Synopsis

The competence of deep learning for the automation and manufacturing sector has received astonishing attention in recent times. The manufacturing industry has recently experienced a revolutionary advancement despite several issues. One of the limitations for technical progress is the bottleneck encountered due to the enormous increase in data volume for processing, comprising various formats, semantics, qualities and features. Deep learning enables detection of meaningful features that are difficult to perform using traditional methods.

The book takes the reader on a technological voyage of the industry 4.0 space. Chapters highlight recent applications of deep learning and the associated challenges and opportunities it presents for automating industrial processes and smart applications.

Chapters introduce the reader to a broad range of topics in deep learning and machine learning. Several deep learning techniques used by industrial professionals are covered, including deep feedforward networks, regularization, optimization algorithms, convolutional networks, sequence modeling, and practical project methodology. Readers will find information on the value of deep learning in applications such as natural language processing, speech recognition, computer vision, online recommendation systems, bioinformatics, and videogames.

The book also discusses prospective research directions that focus on the theory and practical applications of deep learning in industrial automation. Therefore, the book aims to serve as a comprehensive reference guide for industrial consultants interested in industry 4.0, and as a handbook for beginners in data science and advanced computer science courses.