Machine Vision Inspection Systems, Machine Learning-Based Approaches
Machine Vision Inspection Systems, Machine Learning-Based Approaches

Author: Muthukumaran Malarvel

Publisher: John Wiley & Sons

Published: 2021-01-15

Total Pages: 352

ISBN-13: 1119786118

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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.

Machine Vision Inspection Systems, Machine Learning-Based Approaches
Machine Vision Inspection Systems, Machine Learning-Based Approaches

Author: Muthukumaran Malarvel

Publisher: John Wiley & Sons

Published: 2021-01-14

Total Pages: 354

ISBN-13: 111978610X

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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.

Machine Vision Inspection Systems, Machine Learning-Based Approaches
Machine Vision Inspection Systems, Machine Learning-Based Approaches

Author: Muthukumaran Malarvel

Publisher: John Wiley & Sons

Published: 2021-02-24

Total Pages: 354

ISBN-13: 1119786096

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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.

Machine Vision
Machine Vision

Author: Jürgen Beyerer

Publisher: Springer

Published: 2015-10-01

Total Pages: 802

ISBN-13: 3662477947

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The book offers a thorough introduction to machine vision. It is organized in two parts. The first part covers the image acquisition, which is the crucial component of most automated visual inspection systems. All important methods are described in great detail and are presented with a reasoned structure. The second part deals with the modeling and processing of image signals and pays particular regard to methods, which are relevant for automated visual inspection.

Practical Machine Learning for Computer Vision
Practical Machine Learning for Computer Vision

Author: Valliappa Lakshmanan

Publisher: "O'Reilly Media, Inc."

Published: 2021-07-21

Total Pages: 481

ISBN-13: 1098102339

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This practical book shows you how to employ machine learning models to extract information from images. ML engineers and data scientists will learn how to solve a variety of image problems including classification, object detection, autoencoders, image generation, counting, and captioning with proven ML techniques. This book provides a great introduction to end-to-end deep learning: dataset creation, data preprocessing, model design, model training, evaluation, deployment, and interpretability. Google engineers Valliappa Lakshmanan, Martin Görner, and Ryan Gillard show you how to develop accurate and explainable computer vision ML models and put them into large-scale production using robust ML architecture in a flexible and maintainable way. You'll learn how to design, train, evaluate, and predict with models written in TensorFlow or Keras. You'll learn how to: Design ML architecture for computer vision tasks Select a model (such as ResNet, SqueezeNet, or EfficientNet) appropriate to your task Create an end-to-end ML pipeline to train, evaluate, deploy, and explain your model Preprocess images for data augmentation and to support learnability Incorporate explainability and responsible AI best practices Deploy image models as web services or on edge devices Monitor and manage ML models

A Guide for Machine Vision in Quality Control
A Guide for Machine Vision in Quality Control

Author: Sheila Anand

Publisher: CRC Press

Published: 2019-12-23

Total Pages: 193

ISBN-13: 1000753816

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Machine Vision systems combine image processing with industrial automation. One of the primary areas of application of Machine Vision in the Industry is in the area of Quality Control. Machine vision provides fast, economic and reliable inspection that improves quality as well as business productivity. Building machine vision applications is a challenging task as each application is unique, with its own requirements and desired outcome. A Guide to Machine Vision in Quality Control follows a practitioner’s approach to learning machine vision. The book provides guidance on how to build machine vision systems for quality inspections. Practical applications from the Industry have been discussed to provide a good understanding of usage of machine vision for quality control. Real-world case studies have been used to explain the process of building machine vision solutions. The book offers comprehensive coverage of the essential topics, that includes: Introduction to Machine Vision Fundamentals of Digital Images Discussion of various machine vision system components Digital image processing related to quality control Overview of automation The book can be used by students and academics, as well as by industry professionals, to understand the fundamentals of machine vision. Updates to the on-going technological innovations have been provided with a discussion on emerging trends in machine vision and smart factories of the future. Sheila Anand is a PhD graduate and Professor at Rajalakshmi Engineering College, Chennai, India. She has over three decades of experience in teaching, consultancy and research. She has worked in the software industry and has extensive experience in development of software applications and in systems audit of financial, manufacturing and trading organizations. She guides Ph.D. aspirants and many of her research scholars have since been awarded their doctoral degree. She has published many papers in national and international journals and is a reviewer for several journals of repute. L Priya is a PhD graduate working as Associate Professor and Head, Department of Information Technology at Rajalakshmi Engineering College, Chennai, India. She has nearly two decades of teaching experience and good exposure to consultancy and research. She has delivered many invited talks, presented papers and won several paper awards in International Conferences. She has published several papers in International journals and is a reviewer for SCI indexed journals. Her areas of interest include Machine Vision, Wireless Communication and Machine Learning.

Introduction to Machine Learning
Introduction to Machine Learning

Author: Ethem Alpaydin

Publisher: MIT Press

Published: 2014-08-22

Total Pages: 639

ISBN-13: 0262028182

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Introduction -- Supervised learning -- Bayesian decision theory -- Parametric methods -- Multivariate methods -- Dimensionality reduction -- Clustering -- Nonparametric methods -- Decision trees -- Linear discrimination -- Multilayer perceptrons -- Local models -- Kernel machines -- Graphical models -- Brief contents -- Hidden markov models -- Bayesian estimation -- Combining multiple learners -- Reinforcement learning -- Design and analysis of machine learning experiments.

Examining Optoelectronics in Machine Vision and Applications in Industry 4.0
Examining Optoelectronics in Machine Vision and Applications in Industry 4.0

Author: Sergiyenko, Oleg

Publisher: IGI Global

Published: 2021-02-12

Total Pages: 346

ISBN-13: 179986524X

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The research and exploitation of optoelectronic properties in the industrial branch of electronics is becoming more popular each day due to the important role they play in the development of a large variety of sensors, devices, and systems for identifying, measuring, and constructing. While optoelectronics study the applications of electronic devices that source, detect, and transform light, machine vision generates and detects light in order to provide imaging-based automatic inspections and analysis for such applications as automatic object and environmental inspection, process control, and robot/mobile machine guidance in industry. Machine vision is less efficient without optoelectronics, and thus, it is important to investigate the theoretical approaches to different optoelectronic devices available for machine vision as well as current scanning technologies. Examining Optoelectronics in Machine Vision and Applications in Industry 4.0 focuses on the examination of emerging technologies for the design, fabrication, and implementation of optoelectronic sensors, devices, and systems in a machine vision approach to support industrial, commercial, and scientific applications. The book covers topics such as the design, fabrication, and implementation of sensors and devices as well as the development viewpoint of optoelectronic systems and artificial vision techniques using optoelectronic devices. The interaction and informational communication between all these mentioned devices in the complex solution of the same task is the subject of modern challenges in Industry 4.0. Thus, this book supports engineers, technology developers, academicians, researchers, and students who seek machine vision techniques for detection, measurement, and 3D reconstruction.

Computer Vision In Medical Imaging
Computer Vision In Medical Imaging

Author: Chi Hau Chen

Publisher: World Scientific

Published: 2013-11-18

Total Pages: 410

ISBN-13: 9814460958

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The major progress in computer vision allows us to make extensive use of medical imaging data to provide us better diagnosis, treatment and predication of diseases. Computer vision can exploit texture, shape, contour and prior knowledge along with contextual information from image sequence and provide 3D and 4D information that helps with better human understanding. Many powerful tools have been available through image segmentation, machine learning, pattern classification, tracking, reconstruction to bring much needed quantitative information not easily available by trained human specialists. The aim of the book is for both medical imaging professionals to acquire and interpret the data, and computer vision professionals to provide enhanced medical information by using computer vision techniques. The final objective is to benefit the patients without adding to the already high medical costs.

Machine Vision for Industry 4.0
Machine Vision for Industry 4.0

Author: Roshani Raut

Publisher:

Published: 2022

Total Pages:

ISBN-13: 9780367641641

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"This book discusses the use of machine vision and technologies in specific engineering case studies and focuses on how machine vision techniques are impacting every step of industrial processes and how smart sensors and cognitive big data analytics are supporting the automation processes in Industry 4.0 applications. Industry 4.0, the fourth industrial revolution, combines traditional manufacturing with automation and data exchange. Machine vision is used in industry for reliable product inspections, quality control, and data capture solutions. It combines different technologies to provide important information from the acquisition and analysis of images for robot-based inspection and guidance"--