Machine Vision for Industry 4.0: Applications and Case Studies

✍ Scribed by R. Raut, S. Krit, P. Chatterjee

Year: 2022
Tongue: English
Leaves: 323
Category: Library

No coin nor oath required. For personal study only.

✦ Table of Contents

Cover
Half Title
Title Page
Copyright Page
Dedication
Contents
Preface
Acknowledgments
Editors
Contributor
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: The Role of Sensing Techniques in Precision Agriculture
Chapter 4: Perspectives on Deep Learning Techniques for Industrial IoT
Chapter 5: Proposal for Missing Person Locator and Identifier Using Artificial Intelligence and Supercomputing Techniques
Chapter 6: Inclusion of Impaired People in Industry 4.0: An Approach to Recognise 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 Interactions (DDIs) Using Machine Learning Techniques in Drug Development Process
Chapter 10: Image Processing-Based Fire Detection Using IoT Devices
Chapter 11: Crowd Estimation in Trains by Using Machine Vision
Chapter 12: Analysis of a 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
Index

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