Computer Vision, Models and Inspection PDF Download
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Author: A. D. Marshall
Publisher:
ISBN:
Category :
Languages : en
Pages : 437
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Book Description
Author: A David Marshall
Publisher: World Scientific
ISBN: 981452008X
Category : Computers
Languages : en
Pages : 457
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Book Description
The main focus of this book is on the uses of computer vision for inspection and model based matching. It also provides a short, self contained introductory course on computer vision. The authors describe various state-of-the-art approaches to probems and then set forth their proposed approach to matching and inspection. They deal primarily with 3-D vision but also discuss 2-D vision strategies when relevant.The book is suitable for researchers, final year undergraduates and graduate students. Useful review questions at the end of each chapter allow this book to be used for self-study.
Author: A. D. Marshall
Publisher:
ISBN:
Category :
Languages : en
Pages : 437
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Book Description
Author: Jürgen Beyerer
Publisher: Springer
ISBN: 3662477947
Category : Technology & Engineering
Languages : en
Pages : 802
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Book Description
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.
Author: Herbert Freeman
Publisher: Elsevier
ISBN: 0323155588
Category : Technology & Engineering
Languages : en
Pages : 333
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Book Description
Machine Vision for Inspection and Measurement contains the proceedings of the Second Annual Workshop on Machine Vision sponsored by the Center for Computer Aids for Industrial Productivity (CAIP) at Rutgers University and held on April 25-26, 1988 in New Brunswick, New Jersey. The papers explore the application of machine vision to inspection and measurement and cover topics such as the problem of object-pose estimation and depth recovery through inverse optics. The use of machine vision techniques in inspection of integrated circuits and semiconductor wafers is also discussed. Comprised of 11 chapters, this book opens with the problem of using fine-grained parallel machines for VLSI inspection. The discussion then turns to a variety of real-life applications of machine vision, including inspection of integrated circuits, semiconductor wafers, TV-tube glass, and mechanical parts. The use of machine vision to measure the curvature of the human cornea for vision correction and contact lens fitting purposes is also considered. The remaining chapters focus on motion estimation from stereo sequences using orthographic-view algorithms; photometric sampling for determining surface shape and reflectance; and efficient depth recovery by means of inverse optics. A chapter addresses the question of whether the industry is ready for machine vision and comes up with some optimistic predictions. This monograph will be of interest to practitioners in the fields of computer science and applied mathematics.
Author: R. Rosandich
Publisher: Springer Science & Business Media
ISBN: 1461312019
Category : Technology & Engineering
Languages : en
Pages : 311
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Book Description
A great deal of research is being done in the areas of artificial vision and neural networks. Although much of this research has been theoretical in nature, many of the techniques developed through these efforts are now mature enough for use in practical applications. Automated Visual Inspection Using Artificial Neural Networks explains the application of recently emerging technology in the areas of artificial vision and neural networks to automated visual inspection. The information is organised in a clear, informative manner, bridging the gap between theoretical research and practical application. Significantly this book includes: * broad coverage of all aspects of the automated visual inspection problem, * details of the HAVENET neural network and the CAMERA vision model, and * detailed descriptions of practical applications of intelligent visual inspection.
Author: C. H. Chen
Publisher: World Scientific
ISBN: 9812384731
Category : Computers
Languages : en
Pages : 1045
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Book Description
The very significant advances in computer vision and pattern recognition and their applications in the last few years reflect the strong and growing interest in the field as well as the many opportunities and challenges it offers. The second edition of this handbook represents both the latest progress and updated knowledge in this dynamic field. The applications and technological issues are particularly emphasized in this edition to reflect the wide applicability of the field in many practical problems. To keep the book in a single volume, it is not possible to retain all chapters of the first edition. However, the chapters of both editions are well written for permanent reference.
Author: Simon J. D. Prince
Publisher: Cambridge University Press
ISBN: 1139510568
Category : Computers
Languages : en
Pages : 599
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Book Description
This modern treatment of computer vision focuses on learning and inference in probabilistic models as a unifying theme. It shows how to use training data to learn the relationships between the observed image data and the aspects of the world that we wish to estimate, such as the 3D structure or the object class, and how to exploit these relationships to make new inferences about the world from new image data. With minimal prerequisites, the book starts from the basics of probability and model fitting and works up to real examples that the reader can implement and modify to build useful vision systems. Primarily meant for advanced undergraduate and graduate students, the detailed methodological presentation will also be useful for practitioners of computer vision. • Covers cutting-edge techniques, including graph cuts, machine learning and multiple view geometry • A unified approach shows the common basis for solutions of important computer vision problems, such as camera calibration, face recognition and object tracking • More than 70 algorithms are described in sufficient detail to implement • More than 350 full-color illustrations amplify the text • The treatment is self-contained, including all of the background mathematics • Additional resources at www.computervisionmodels.com
Author: IS & T--the Society for Imaging Science and Technology
Publisher: SPIE-International Society for Optical Engineering
ISBN: 9780819435842
Category : Business & Economics
Languages : en
Pages : 410
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Book Description
Author: Valliappa Lakshmanan
Publisher: "O'Reilly Media, Inc."
ISBN: 1098102339
Category : Computers
Languages : en
Pages : 481
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Book Description
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
Author: Sencer Yeralan
Publisher:
ISBN:
Category :
Languages : en
Pages :
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Book Description
