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Machine Vision Inspection Systems Machine Learningbased Approaches Muthukumaran Malarvel Soumya Ranjan Nayak Prasant Kumar Pattnaik Surya Narayan Panda

  • SKU: BELL-23509636
Machine Vision Inspection Systems Machine Learningbased Approaches Muthukumaran Malarvel Soumya Ranjan Nayak Prasant Kumar Pattnaik Surya Narayan Panda
$ 31.00 $ 45.00 (-31%)

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Machine Vision Inspection Systems Machine Learningbased Approaches Muthukumaran Malarvel Soumya Ranjan Nayak Prasant Kumar Pattnaik Surya Narayan Panda instant download after payment.

Publisher: John Wiley & Sons
File Extension: PDF
File size: 39.87 MB
Pages: 352
Author: Muthukumaran Malarvel; Soumya Ranjan Nayak; Prasant Kumar Pattnaik; Surya Narayan Panda
ISBN: 9781119786092, 1119786096
Language: English
Year: 2021
Volume: 2

Product desciption

Machine Vision Inspection Systems Machine Learningbased Approaches Muthukumaran Malarvel Soumya Ranjan Nayak Prasant Kumar Pattnaik Surya Narayan Panda by Muthukumaran Malarvel; Soumya Ranjan Nayak; Prasant Kumar Pattnaik; Surya Narayan Panda 9781119786092, 1119786096 instant download after payment.

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.

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