Machine Vision for Industry 4.0 - Roshani Raut

Machine Vision for Industry 4.0

Applications and Case Studies

Roshani Raut (Redaktør) ; Prasenjit Chatterjee (Redaktør) ; Salahddine Krit (Redaktør)

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Vår pris: 1688,-

(Innbundet) Fri frakt!
Leveringstid: Sendes innen 21 dager

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Utgitt:
Forlag: CRC Press
Innbinding: Innbundet
Språk: Engelsk
Sider: 302
ISBN: 9780367637125
Format: 23 x 16 cm
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VURDERING
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Les vurderinger
Chapter 1. Challenges in Industry 4.0 for Machine Vision: A Conceptual Framework, A Review, and Numerous case studies, Chapter 2. Practical issues in robotics internet of things, Chapter 3. Role of sensing techniques in precision agriculture, Chapter 4. Perspectives on Deep Learning Techniques for Industrial IoT, Chapter 5. Missing person locator and identifier using artificial intelligence and supercomputing techniques proposal, Chapter 6. Inclusion of Impaired People in Industry 4.0: An Approach to Recognize Orders of Deaf-mute Supervisors through an Intelligent Sign Language Recognition System, Chapter 7. A Deep Learning Approach to Classify the Causes of Depression from Reddit Posts, Chapter 8. Psychiatric ChatBOT for COVID-19 using Machine Learning Approaches, Chapter 9. An Analysis of Drug – Drug Interaction (DI) using Machine Learning Techniques in Drug Development Process, Chapter 10. Image Processing based Fire Detection using IOT devices, Chapter 11. Crowd Estimation in Train by using Machine Vision, Chapter 12. Analysis of Machine Learning Algorithm to predict Wine Quality, Chapter 13. Machine Vision in Industry 4.0: Applications, Challenges and Future Directions, Chapter 14. Industry 5.0: The Integration of Modern Technologies
Dr. Roshani Raut is an Associate Professor in the Department of Information Technology and also handling the charge of Associate Dean International Relations at Pimpri Chinchwad College of Engineering, Pune, India. She completed her doctorate in computer science and engineering. She has more than 17 years of experience and is a member of ACM and ISTE. She has availed the research and workshop grants from BCUD, Pune University. She has presented more than 70 research communications in national and international conferences and journals and published 15 patents. She has been invited as a TPC member and session chair for various national and international conferences. She has served as editor for various books of IGI Global, CRC Press/Taylor & Francis, and Scrivener Wiley, etc. Her research area includes Artificial Intelligence, Machine Learning, Data Mining, Deep Learning, Internet of Things, and so on. Her details are available on https://roshaniraut531.wixsite.com/roshaniraut/


Dr. Salah-ddine Krit is an Associate Professor at the Polydisciplinary Faculty of Ouarzazate, Ibn Zohr University Agadir Morocco, He is currently the Director of Engineering Science and Energies Laboratory and the Chief of the Department of Mathematics, Informatics and Management. He received his PhD in software engineering from Sidi Mohammed Ben Abdellah University, Fez, Morroco. He worked as an Engineer Team Leader in audio and power management integrated circuits research, design, simulation and layout of analog and digital blocks dedicated for mobile and satellite communication systems. He has authored and co-authored over 130 journal articles, proceedings, and book chapters published by reputable publishers.


Dr. Prasenjit Chatterjee is an Associate Professor of Mechanical Engineering Department at the MCKV Institute of Engineering, India. He has published over 80 research papers in various international journals and has received numerous awards including Outstanding Researcher Award and University Gold Medal. He has been the guest editor of several special issues and has edited and authored several books on decision-making approaches and sustainability. He is the Lead Series Editor of International Perspectives on Decision Analysis and Operations Research, Emerald Group Publishing. Dr. Chatterjee is one of the developers of a new data-driven multiple-criteria decision-making method called Measurement of Alternatives and Ranking according to Compromise Solution (MARCOS).