Machine Vision Inspection Systems: Volume 2: Machine Learning-Based Approaches

ISBN 10: 1119786096 / ISBN 13: 9781119786092

Published by Wiley-Scrivener, 2021

About this Item

Machine Vision Inspection Systems: Volume 2: Machine Learning-Based Approaches In englischer Sprache. pages.

Seller Inventory # BN404477

Bibliographic Details

• Title: Machine Vision Inspection Systems: Volume 2: Machine Learning-Based Approaches
• Publisher: Wiley-Scrivener
• Publication Date: 2021
• Language: English
• ISBN 10: 1119786096
• ISBN 13: 9781119786092
• Binding: Hardcover
• Edition: 2nd Edition
• Condition: gut
• Weight: 2000 grams

About this title

Synopsis

Machine Vision Inspection Systems (MVIS) is a multidisciplinary research field that emphasizes image processing, machine vision and, pattern recognition for industrial applications. Inspection techniques are generally used in destructive and non-destructive evaluation industry. Now a day's the current research on machine inspection gained more popularity among various researchers, because the manual assessment of the inspection may fail and turn into false assessment due to a large number of examining while inspection process.

This volume 2 covers machine learning-based approaches in MVIS applications and it can be employed to a wide diversity of problems particularly in Non-Destructive testing (NDT), presence/absence detection, defect/fault detection (weld, textile, tiles, wood, etc.), automated vision test & measurement, pattern matching, optical character recognition & verification (OCR/OCV), natural language processing, medical diagnosis, etc. This edited book is designed to address various aspects of recent methodologies, concepts, and research plan out to the readers for giving more depth insights for perusing research on machine vision using machine learning-based approaches.

About the Author

Muthukumaran Malarvel obtained his PhD in digital image processing and he is currently working as an associate professor in the Department of Computer Science and Engineering at Chitkara University, Punjab, India. His research interests include digital image processing, machine vision systems, image statistical analysis & feature extraction, and machine learning algorithms.

Soumya Ranjan Nayak obtained his PhD in computer science and engineering from the Biju Patnaik University of Technology, India. He has more than a decade of teaching and research experience and currently is working as an assistant professor, Amity University, Noida, India. His research interests include image analysis on fractal geometry, color and texture analysis jointly and separately.

Prasant Kumar Pattnaik PhD (Computer Science), Fellow IETE, Senior Member IEEE is a Professor at the School of Computer Engineering, KIIT Deemed to be University, Bhubaneswar, India. He has more than a decade of teaching and research experience. His areas of interest include mobile computing, cloud computing, cyber security, intelligent systems and brain computer interface.

Surya Narayan Panda is a Professor and Director Research at Chitkara University, Punjab, India. His areas of interest include cybersecurity, networking, advanced computer networks, machine learning, and artificial intelligence. He has developed the prototype of Smart Portable Intensive Care Unit through which the doctor can provide immediate virtual medical assistance to emergency cases in the ambulance. He is currently involved in designing different healthcare devices for real-time issues using AI and ML.