Author: Patrick Henry Winston
Publisher: McGraw-Hill Companies
ISBN:
Category : Computers
Languages : en
Pages : 296
Book Description
The Psychology of Computer Vision
Author: Patrick Henry Winston
Publisher: McGraw-Hill Companies
ISBN:
Category : Computers
Languages : en
Pages : 296
Book Description
Publisher: McGraw-Hill Companies
ISBN:
Category : Computers
Languages : en
Pages : 296
Book Description
Computer Vision
Author: Simon J. D. Prince
Publisher: Cambridge University Press
ISBN: 1107011795
Category : Computers
Languages : en
Pages : 599
Book Description
A modern treatment focusing on learning and inference, with minimal prerequisites, real-world examples and implementable algorithms.
Publisher: Cambridge University Press
ISBN: 1107011795
Category : Computers
Languages : en
Pages : 599
Book Description
A modern treatment focusing on learning and inference, with minimal prerequisites, real-world examples and implementable algorithms.
Biological and Computer Vision
Author: Gabriel Kreiman
Publisher: Cambridge University Press
ISBN: 1108483437
Category : Computers
Languages : en
Pages : 275
Book Description
This book introduces neural mechanisms of biological vision and how artificial intelligence algorithms learn to interpret images.
Publisher: Cambridge University Press
ISBN: 1108483437
Category : Computers
Languages : en
Pages : 275
Book Description
This book introduces neural mechanisms of biological vision and how artificial intelligence algorithms learn to interpret images.
Object Categorization
Author: Sven J. Dickinson
Publisher: Cambridge University Press
ISBN: 0521887380
Category : Computers
Languages : en
Pages : 553
Book Description
A unique multidisciplinary perspective on the problem of visual object categorization.
Publisher: Cambridge University Press
ISBN: 0521887380
Category : Computers
Languages : en
Pages : 553
Book Description
A unique multidisciplinary perspective on the problem of visual object categorization.
Infrastructure Computer Vision
Author: Ioannis Brilakis
Publisher: Butterworth-Heinemann
ISBN: 0128172584
Category : Technology & Engineering
Languages : en
Pages : 410
Book Description
Infrastructure Computer Vision delves into this field of computer science that works on enabling computers to see, identify, process images and provide appropriate output in the same way that human vision does. However, implementing these advanced information and sensing technologies is difficult for many engineers. This book provides civil engineers with the technical detail of this advanced technology and how to apply it to their individual projects. - Explains how to best capture raw geometrical and visual data from infrastructure scenes and assess their quality - Offers valuable insights on how to convert the raw data into actionable information and knowledge stored in Digital Twins - Bridges the gap between the theoretical aspects and real-life applications of computer vision
Publisher: Butterworth-Heinemann
ISBN: 0128172584
Category : Technology & Engineering
Languages : en
Pages : 410
Book Description
Infrastructure Computer Vision delves into this field of computer science that works on enabling computers to see, identify, process images and provide appropriate output in the same way that human vision does. However, implementing these advanced information and sensing technologies is difficult for many engineers. This book provides civil engineers with the technical detail of this advanced technology and how to apply it to their individual projects. - Explains how to best capture raw geometrical and visual data from infrastructure scenes and assess their quality - Offers valuable insights on how to convert the raw data into actionable information and knowledge stored in Digital Twins - Bridges the gap between the theoretical aspects and real-life applications of computer vision
Computer Vision for Assistive Healthcare
Author: Leo Marco
Publisher: Academic Press
ISBN: 0128134461
Category : Technology & Engineering
Languages : en
Pages : 398
Book Description
Computer Vision for Assistive Healthcare describes how advanced computer vision techniques provide tools to support common human needs, such as mental functioning, personal mobility, sensory functions, daily living activities, image processing, pattern recognition, machine learning and how language processing and computer graphics cooperate with robotics to provide such tools. Users will learn about the emerging computer vision techniques for supporting mental functioning, algorithms for analyzing human behavior, and how smart interfaces and virtual reality tools lead to the development of advanced rehabilitation systems able to perform human action and activity recognition. In addition, the book covers the technology behind intelligent wheelchairs, how computer vision technologies have the potential to assist blind people, and about the computer vision-based solutions recently employed for safety and health monitoring. - Gives the state-of-the-art computer vision techniques and tools for assistive healthcare - Includes a broad range of topic areas, ranging from image processing, pattern recognition, machine learning to robotics, natural language processing and computer graphics - Presents a wide range of application areas, ranging from mobility, sensory substitution, and safety and security, to mental and physical rehabilitation and training - Written by leading researchers in this growing field of research - Describes the outstanding research challenges that still need to be tackled, giving researchers good indicators of research opportunities
Publisher: Academic Press
ISBN: 0128134461
Category : Technology & Engineering
Languages : en
Pages : 398
Book Description
Computer Vision for Assistive Healthcare describes how advanced computer vision techniques provide tools to support common human needs, such as mental functioning, personal mobility, sensory functions, daily living activities, image processing, pattern recognition, machine learning and how language processing and computer graphics cooperate with robotics to provide such tools. Users will learn about the emerging computer vision techniques for supporting mental functioning, algorithms for analyzing human behavior, and how smart interfaces and virtual reality tools lead to the development of advanced rehabilitation systems able to perform human action and activity recognition. In addition, the book covers the technology behind intelligent wheelchairs, how computer vision technologies have the potential to assist blind people, and about the computer vision-based solutions recently employed for safety and health monitoring. - Gives the state-of-the-art computer vision techniques and tools for assistive healthcare - Includes a broad range of topic areas, ranging from image processing, pattern recognition, machine learning to robotics, natural language processing and computer graphics - Presents a wide range of application areas, ranging from mobility, sensory substitution, and safety and security, to mental and physical rehabilitation and training - Written by leading researchers in this growing field of research - Describes the outstanding research challenges that still need to be tackled, giving researchers good indicators of research opportunities
Computational Vision
Author: Hanspeter A. Mallot
Publisher: MIT Press
ISBN: 9780262133814
Category : Medical
Languages : en
Pages : 318
Book Description
This text provides an introduction to computational aspects of early vision, in particular, color, stereo, and visual navigation. It integrates approaches from psychophysics and quantitative neurobiology, as well as theories and algorithms from machine vision and photogrammetry. When presenting mathematical material, it uses detailed verbal descriptions and illustrations to clarify complex points. The text is suitable for upper-level students in neuroscience, biology, and psychology who have basic mathematical skills and are interested in studying the mathematical modeling of perception.
Publisher: MIT Press
ISBN: 9780262133814
Category : Medical
Languages : en
Pages : 318
Book Description
This text provides an introduction to computational aspects of early vision, in particular, color, stereo, and visual navigation. It integrates approaches from psychophysics and quantitative neurobiology, as well as theories and algorithms from machine vision and photogrammetry. When presenting mathematical material, it uses detailed verbal descriptions and illustrations to clarify complex points. The text is suitable for upper-level students in neuroscience, biology, and psychology who have basic mathematical skills and are interested in studying the mathematical modeling of perception.
Vision
Author: David Marr
Publisher: MIT Press
ISBN: 0262514621
Category : Psychology
Languages : en
Pages : 429
Book Description
Available again, an influential book that offers a framework for understanding visual perception and considers fundamental questions about the brain and its functions. David Marr's posthumously published Vision (1982) influenced a generation of brain and cognitive scientists, inspiring many to enter the field. In Vision, Marr describes a general framework for understanding visual perception and touches on broader questions about how the brain and its functions can be studied and understood. Researchers from a range of brain and cognitive sciences have long valued Marr's creativity, intellectual power, and ability to integrate insights and data from neuroscience, psychology, and computation. This MIT Press edition makes Marr's influential work available to a new generation of students and scientists. In Marr's framework, the process of vision constructs a set of representations, starting from a description of the input image and culminating with a description of three-dimensional objects in the surrounding environment. A central theme, and one that has had far-reaching influence in both neuroscience and cognitive science, is the notion of different levels of analysis—in Marr's framework, the computational level, the algorithmic level, and the hardware implementation level. Now, thirty years later, the main problems that occupied Marr remain fundamental open problems in the study of perception. Vision provides inspiration for the continuing efforts to integrate knowledge from cognition and computation to understand vision and the brain.
Publisher: MIT Press
ISBN: 0262514621
Category : Psychology
Languages : en
Pages : 429
Book Description
Available again, an influential book that offers a framework for understanding visual perception and considers fundamental questions about the brain and its functions. David Marr's posthumously published Vision (1982) influenced a generation of brain and cognitive scientists, inspiring many to enter the field. In Vision, Marr describes a general framework for understanding visual perception and touches on broader questions about how the brain and its functions can be studied and understood. Researchers from a range of brain and cognitive sciences have long valued Marr's creativity, intellectual power, and ability to integrate insights and data from neuroscience, psychology, and computation. This MIT Press edition makes Marr's influential work available to a new generation of students and scientists. In Marr's framework, the process of vision constructs a set of representations, starting from a description of the input image and culminating with a description of three-dimensional objects in the surrounding environment. A central theme, and one that has had far-reaching influence in both neuroscience and cognitive science, is the notion of different levels of analysis—in Marr's framework, the computational level, the algorithmic level, and the hardware implementation level. Now, thirty years later, the main problems that occupied Marr remain fundamental open problems in the study of perception. Vision provides inspiration for the continuing efforts to integrate knowledge from cognition and computation to understand vision and the brain.
Practical Machine Learning for Computer Vision
Author: Valliappa Lakshmanan
Publisher: "O'Reilly Media, Inc."
ISBN: 1098102339
Category : Computers
Languages : en
Pages : 481
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
Publisher: "O'Reilly Media, Inc."
ISBN: 1098102339
Category : Computers
Languages : en
Pages : 481
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
Object Recognition
Author: M. Bennamoun
Publisher: Springer Science & Business Media
ISBN: 9781852333980
Category : Computers
Languages : en
Pages : 376
Book Description
Automatie object recognition is a multidisciplinary research area using con cepts and tools from mathematics, computing, optics, psychology, pattern recognition, artificial intelligence and various other disciplines. The purpose of this research is to provide a set of coherent paradigms and algorithms for the purpose of designing systems that will ultimately emulate the functions performed by the Human Visual System (HVS). Hence, such systems should have the ability to recognise objects in two or three dimensions independently of their positions, orientations or scales in the image. The HVS is employed for tens of thousands of recognition events each day, ranging from navigation (through the recognition of landmarks or signs), right through to communication (through the recognition of characters or people themselves). Hence, the motivations behind the construction of recognition systems, which have the ability to function in the real world, is unquestionable and would serve industrial (e.g. quality control), military (e.g. automatie target recognition) and community needs (e.g. aiding the visually impaired). Scope, Content and Organisation of this Book This book provides a comprehensive, yet readable foundation to the field of object recognition from which research may be initiated or guided. It repre sents the culmination of research topics that I have either covered personally or in conjunction with my PhD students. These areas include image acqui sition, 3-D object reconstruction, object modelling, and the matching of ob jects, all of which are essential in the construction of an object recognition system.
Publisher: Springer Science & Business Media
ISBN: 9781852333980
Category : Computers
Languages : en
Pages : 376
Book Description
Automatie object recognition is a multidisciplinary research area using con cepts and tools from mathematics, computing, optics, psychology, pattern recognition, artificial intelligence and various other disciplines. The purpose of this research is to provide a set of coherent paradigms and algorithms for the purpose of designing systems that will ultimately emulate the functions performed by the Human Visual System (HVS). Hence, such systems should have the ability to recognise objects in two or three dimensions independently of their positions, orientations or scales in the image. The HVS is employed for tens of thousands of recognition events each day, ranging from navigation (through the recognition of landmarks or signs), right through to communication (through the recognition of characters or people themselves). Hence, the motivations behind the construction of recognition systems, which have the ability to function in the real world, is unquestionable and would serve industrial (e.g. quality control), military (e.g. automatie target recognition) and community needs (e.g. aiding the visually impaired). Scope, Content and Organisation of this Book This book provides a comprehensive, yet readable foundation to the field of object recognition from which research may be initiated or guided. It repre sents the culmination of research topics that I have either covered personally or in conjunction with my PhD students. These areas include image acqui sition, 3-D object reconstruction, object modelling, and the matching of ob jects, all of which are essential in the construction of an object recognition system.