Bentham Science Publishers
The competence of DL for automation and manufacturing sector has received astonishing attention during past decade. The manufacturing industry has recently experienced a revolutionary advancement despite several issues. One of the prime hindrances is enormous increase in the data comprising of various formats, semantics, qualities and features. DL enables detection of meaningful features that were far difficult to perform through traditional methods so far. The goal of the book Challenges and Opportunities for Deep Learning Applications in Industry 4.0 is to present the challenges and opportunities in smart industry. The book also discusses the prospective research directions that focus on the theory and practical applications of DL in industrial automation.
The book introduces a broad range of topics in deep learning and machine learning. It describes deep learning techniques used by practitioners in industry, including deep feed forward networks, regularization, optimization algorithms, convolutional networks, sequence modeling, and practical methodology; and it surveys such applications as natural language processing, speech recognition, computer vision, online recommendation systems, bioinformatics, and videogames. Hence, the book aims to serve as a complete handbook and research guide to the readers working in this domain.
About the editors:
Dr. Vaishali Mehta graduated as B.Tech in Computer Science & Engineering from Maharishi Dayanand Universit in 2003 and received Masters in Information Technology from Kurukshetra University in 2009. She has completed PhD in Computer Science and Engineering from Thapar University Patiala in 2018. Currently, she is working as Professor in the Department Information Technology at Panipat Institute of Engineering and Technology, Panipat, Haryana. She has 19 years of teaching experience at undergraduate and postgraduate level. Her research interests include approximation algorithms, location modeling, IoT, data science, artificial intelligence and machine learning. She has published research articles in quality journals (SCI and Scopus indexed), national and international conferences and books of reputed publishers. She has supervised many projects at UG and PG level. She is life member of IEEE society. She is editing several books with reputed publishers like CRC/Taylor & Francis, Scivener – Wiley & Sons, Bentham Science etc. She has reviewed research papers of reputed journals and conferences. She has four patents published to her credit.
Dr. Dolly Sharma graduated as B.Tech in Computer Science & Engineering from Kurukshetra University in 2004 and received Masters in Information Technology with honors from Panjab University, Chandigarh in 2007. She was the second University topper. She has completed PhD in Computer Science and Engineering from Punjab Engineering College, Chandigarh. She is currently working as Associate Professor in Amity University, Noida. She has a rich teaching experience of around 16 years. Her area of interests includes Bioinformatics, Grid Computing and Data Mining. She has published a number of research papers and book chapters indexed in SCOPUS and SCI. She has also published a few authored and edited books. She has contributed as a reviewer in important conferences and Journals. She has chaired International Conferences and delivered invited talks. She is a life time member of ISTE and AIENG.
Dr. Monika Mangla received her Ph.D. from Thapar Institute of Engineering & Technology, Patiala, Punjab, in the year 2019. Currently, she is working as an associate Professor in the department of Information Technology at Dwarkadas J Sanghvi College of Engineering, Mumbai. She has 20 years of teaching experience at undergraduate and postgraduate level to her credit. Her interest areas include IoT, Cloud Computing, Algorithms and optimization, Location Modelling and Machine Learning. She has guided many projects at UG and PG level. She has also been invited as expert speaker for many workshops. She has published several research papers and book chapters (SCI and Scopus Indexed) with reputed publishers. She is also editor of a book on the topic of Internet of Things to be published by Apple Academic Press, CRC Press, and Apple Academic Press. She has also been associated with several SCI indexed journals like TUBITAK, IMDS etc. as reviewer. She has been associated with several reputed conference as a Session chair. She has also qualified the UGC-NET for Computer Science in July 2018. She has two patents applied to her credit. She is life member of CSI and IETE.
Dr. Anita Gehlot is associated with Uttaranchal University as Professor and Head (Research & Innovation) with more than fifteen years of experience in academics. Her area of expertise includes embedded systems, wireless sensor networks, and Internet of Things. She has been featured among top ten inventors for ten years 2010-2020, by Clarivate Analytics in “India’s Innovation Synopsis” in March 2021. She has filed more than three hundred patents including forty four Indian & International patent grants, 5 PCT and published more than two hundred research papers in SCI/Scopus Journals.
She has authored/edited thirty four books in the area of Embedded Systems and Internet of Things with reputed publishers.
Dr. Rajesh Singh is associated with Uttaranchal University as Director (Research & Innovation) with more than Seventeen years of experience in academics. His area of expertise includes embedded systems, robotics, wireless sensor networks, Internet of Things and Machine Learning. He has been featured 2nd among top ten inventors for ten years 2010-2020, by Clarivate Analytics in “India’s Innovation Synopsis” in March 2021. He has filed more than four hundred patents, including forty four Indian & International patent grants, 5 PCT and published more than two hundred and fifty research papers in SCI/Scopus Journals.
He has authored/edited thirty six books in the area of Embedded Systems and Internet of Things with reputed publishers. He has been featured by Indian and International media for smart systems and devices designed by him to prevent COVID-19 as per WHO guidelines.
Sergio Marquez Sanchez is Industrial Engineer since 2017 from the University of Salamanca. At the same University he obtained his Technical Engineering degree, specialising in Mechanics (2014). At the same time, he obtained a master's degree in design, delineation and finite element analysis with Autodesk Inventor, SolidWorks and CATIA V5. He has worked as a teacher of robotics, programming and 3D design as well as participating in various projects of entrepreneurship, R & D and product design in fields such as educational robotics and wearable technology. His research interests include Smart Textiles, Electronic Textiles, Machine Learning, Robotics, IoT, CNC technologies, PLM Software and Circuit Printing. He is having more than 8 years of teaching experience. He has published several papers in quality journals. National and international conferences. He has reviewed research papers of reputed journals and conferences.
Keywords:
Artificial Intelligence, Machine Learning, Deep Learning, Blockchain, Neural Networks, Machine Learning Applications in Healthcare,Machine Learning Applications in Agriculture,Machine Learning Applications in Industry Automation,Machine Learning Applications in Finance, Machine Learning Applications in Computer Vision and Image Processing.
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Copyright © 2023 by the American Association for the Advancement of Science (AAAS)
