Vtome.ru - электронная библиотека

Machine Vision Inspection Systems Vol.2: Machine Learning-Based Approaches

  • Добавил: buratino
  • Дата: 10-02-2021, 13:49
  • Комментариев: 0
Название: Machine Vision Inspection Systems: Machine Learning-Based Approaches (Machine Vision Inspection Systems, Volume 2)
Автор: Muthukumaran Malarvel (Editor), Soumya Ranjan Nayak (Editor), Prasant Kumar Pattnaik (Editor)
Издательство: Wiley
Год: 2021
Формат: True PDF
Страниц: 337
Размер: 28.4 Mb
Язык: English

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.












НЕ РАБОТАЕТ TURBOBIT.NET? ЕСТЬ РЕШЕНИЕ, ЖМИ СЮДА!


ПРАВООБЛАДАТЕЛЯМ


СООБЩИТЬ ОБ ОШИБКЕ ИЛИ НЕ РАБОЧЕЙ ССЫЛКЕ



Внимание
Уважаемый посетитель, Вы зашли на сайт как незарегистрированный пользователь.
Мы рекомендуем Вам зарегистрироваться либо войти на сайт под своим именем.
Информация
Посетители, находящиеся в группе Гости, не могут оставлять комментарии к данной публикации.