Computational Knowledge Vision
Computational Knowledge Vision

Author: Wenbo Zheng

Publisher: Elsevier

Published: 2024-08-19

Total Pages: 278

ISBN-13: 0443216185

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Computational Knowledge Vision: The First Footprints presents a novel, advanced framework which combines structuralized knowledge and visual models. In advanced image and visual perception studies, a visual model's understanding and reasoning ability often determines whether it works well in complex scenarios. This book presents state-of-the-art mainstream vision models for visual perception. As computer vision is one of the key gateways to artificial intelligence and a significant component of modern intelligent systems, this book delves into computer vision systems that are highly specialized and very limited in their ability to do visual reasoning and causal inference. Questions naturally arise in this arena, including (1) How can human knowledge be incorporated with visual models? (2) How does human knowledge promote the performance of visual models? To address these problems, this book proposes a new framework for computer vision–computational knowledge vision. - Presents a concept and basic framework of Computational Knowledge Vision that extends the knowledge engineering methodology to the computer vision field - Discusses neural networks, meta-learning, graphs, and Transformer models - Illustrates a basic framework for Computational Knowledge Vision whose essential techniques include structuralized knowledge, knowledge projection, and conditional feedback

Vision
Vision

Author: David Marr

Publisher: MIT Press

Published: 2010-07-09

Total Pages: 429

ISBN-13: 0262514621

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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.

Computational Models for Cognitive Vision
Computational Models for Cognitive Vision

Author: Hiranmay Ghosh

Publisher: John Wiley & Sons

Published: 2020-07-01

Total Pages: 244

ISBN-13: 1119527899

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Learn how to apply cognitive principles to the problems of computer vision Computational Models for Cognitive Vision formulates the computational models for the cognitive principles found in biological vision, and applies those models to computer vision tasks. Such principles include perceptual grouping, attention, visual quality and aesthetics, knowledge-based interpretation and learning, to name a few. The author’s ultimate goal is to provide a framework for creation of a machine vision system with the capability and versatility of the human vision. Written by Dr. Hiranmay Ghosh, the book takes readers through the basic principles and the computational models for cognitive vision, Bayesian reasoning for perception and cognition, and other related topics, before establishing the relationship of cognitive vision with the multi-disciplinary field broadly referred to as “artificial intelligence”. The principles are illustrated with diverse application examples in computer vision, such as computational photography, digital heritage and social robots. The author concludes with suggestions for future research and salient observations about the state of the field of cognitive vision. Other topics covered in the book include: · knowledge representation techniques · evolution of cognitive architectures · deep learning approaches for visual cognition Undergraduate students, graduate students, engineers, and researchers interested in cognitive vision will consider this an indispensable and practical resource in the development and study of computer vision.

Machine Learning in Computer Vision
Machine Learning in Computer Vision

Author: Nicu Sebe

Publisher: Springer Science & Business Media

Published: 2005-10-04

Total Pages: 253

ISBN-13: 1402032757

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The goal of this book is to address the use of several important machine learning techniques into computer vision applications. An innovative combination of computer vision and machine learning techniques has the promise of advancing the field of computer vision, which contributes to better understanding of complex real-world applications. The effective usage of machine learning technology in real-world computer vision problems requires understanding the domain of application, abstraction of a learning problem from a given computer vision task, and the selection of appropriate representations for the learnable (input) and learned (internal) entities of the system. In this book, we address all these important aspects from a new perspective: that the key element in the current computer revolution is the use of machine learning to capture the variations in visual appearance, rather than having the designer of the model accomplish this. As a bonus, models learned from large datasets are likely to be more robust and more realistic than the brittle all-design models.

New Trends in Computational Vision and Bio-inspired Computing
New Trends in Computational Vision and Bio-inspired Computing

Author: S. Smys

Publisher: Springer Nature

Published: 2020-09-27

Total Pages: 1664

ISBN-13: 3030418626

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This volume gathers selected, peer-reviewed original contributions presented at the International Conference on Computational Vision and Bio-inspired Computing (ICCVBIC) conference which was held in Coimbatore, India, on November 29-30, 2018. The works included here offer a rich and diverse sampling of recent developments in the fields of Computational Vision, Fuzzy, Image Processing and Bio-inspired Computing. The topics covered include computer vision; cryptography and digital privacy; machine learning and artificial neural networks; genetic algorithms and computational intelligence; the Internet of Things; and biometric systems, to name but a few. The applications discussed range from security, healthcare and epidemic control to urban computing, agriculture and robotics. In this book, researchers, graduate students and professionals will find innovative solutions to real-world problems in industry and society as a whole, together with inspirations for further research.

Advances in Computational Vision and Robotics
Advances in Computational Vision and Robotics

Author: George A. Tsihrintzis

Publisher: Springer Nature

Published: 2023-11-13

Total Pages: 549

ISBN-13: 3031386515

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Advances in Computational Vision and Robotics contains research papers from diverse field of engineering, computer science, social and bio-medical science. This book contains various research articles from the following domain: i. Pattern recognition and Robotic Vision. ii. Artificial Intelligence and Deep Learning application. iii. Big Data Application in Robotics. iv. Deep Learning and Neural Network. Authors from the area of Particle Swarm Optimization, Defect Detection, Gesture Information Collection, Image Processing and Remote Sensing, Melody Recognition, Convolution Neural Network and Satellite Image processing etc. have contributed their research outcomes.

Computational Models of Visual Processing
Computational Models of Visual Processing

Author: Michael S. Landy

Publisher: MIT Press

Published: 1991

Total Pages: 420

ISBN-13: 9780262121552

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The more than twenty contributions in this book, all new and previously unpublished, provide an up-to-date survey of contemporary research on computational modeling of the visual system. The approaches represented range from neurophysiology to psychophysics, and from retinal function to the analysis of visual cues to motion, color, texture, and depth. The contributions are linked thematically by a consistent consideration of the links between empirical data and computational models in the study of visual function. An introductory chapter by Edward Adelson and James Bergen gives a new and elegant formalization of the elements of early vision. Subsequent sections treat receptors and sampling, models of neural function, detection and discrimination, color and shading, motion and texture, and 3D shape. Each section is introduced by a brief topical review and summary. ContributorsEdward H. Adelson, Albert J. Ahumada, Jr., James R. Bergen, David G. Birch, David H. Brainard, Heinrich H. Bülthoff, Charles Chubb, Nancy J. Coletta, Michael D'Zmura, John P. Frisby, Norma Graham, Norberto M. Grzywacz, P. William Haake, Michael J. Hawken, David J. Heeger, Donald C. Hood, Elizabeth B. Johnston, Daniel Kersten, Michael S. Landy, Peter Lennie, J. Stephen Mansfield, J. Anthony Movshon, Jacob Nachmias, Andrew J. Parker, Denis G. Pelli, Stephen B. Pollard, R. Clay Reid, Robert Shapley, Carlo L. M. Tiana, Brian A. Wandell, Andrew B. Watson, David R. Williams, Hugh R. Wilson, Yuede. Yang, Alan L. Yuille

Proceedings of the International Conference on ISMAC in Computational Vision and Bio-Engineering 2018 (ISMAC-CVB)
Proceedings of the International Conference on ISMAC in Computational Vision and Bio-Engineering 2018 (ISMAC-CVB)

Author: Durai Pandian

Publisher: Springer

Published: 2019-01-01

Total Pages: 1869

ISBN-13: 3030006654

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These are the proceedings of the International Conference on ISMAC-CVB, held in Palladam, India, in May 2018. The book focuses on research to design new analysis paradigms and computational solutions for quantification of information provided by object recognition, scene understanding of computer vision and different algorithms like convolutional neural networks to allow computers to recognize and detect objects in images with unprecedented accuracy and to even understand the relationships between them. The proceedings treat the convergence of ISMAC in Computational Vision and Bioengineering technology and includes ideas and techniques like 3D sensing, human visual perception, scene understanding, human motion detection and analysis, visualization and graphical data presentation and a very wide range of sensor modalities in terms of surveillance, wearable applications, home automation etc. ISMAC-CVB is a forum for leading academic scientists, researchers and research scholars to exchange and share their experiences and research results about all aspects of computational vision and bioengineering.

Innovations in Computational Intelligence and Computer Vision
Innovations in Computational Intelligence and Computer Vision

Author: Satyabrata Roy

Publisher: Springer Nature

Published: 2022-05-14

Total Pages: 611

ISBN-13: 9811904758

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This book presents high-quality, peer-reviewed papers from the International Conference on “Innovations in Computational Intelligence and Computer Vision (ICICV 2021),” hosted by Manipal University Jaipur, Rajasthan, India, on August 5–6, 2021. Offering a collection of innovative ideas from researchers, scientists, academics, industry professionals and students, the book covers a variety of topics, such as artificial intelligence and computer vision, image processing and video analysis, applications and services of artificial intelligence and computer vision, interdisciplinary areas combining artificial intelligence and computer vision, and other innovative practices.

Innovations in Computational Intelligence and Computer Vision
Innovations in Computational Intelligence and Computer Vision

Author: Manoj Kumar Sharma

Publisher: Springer Nature

Published: 2020-09-21

Total Pages: 623

ISBN-13: 9811560676

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This book presents high-quality, peer-reviewed papers from the International Conference on “Innovations in Computational Intelligence and Computer Vision (ICICV 2020),” hosted by Manipal University Jaipur, Rajasthan, India, on January 17–19, 2020. Offering a collection of innovative ideas from researchers, scientists, academics, industry professionals and students, the book covers a variety of topics, such as artificial intelligence and computer vision, image processing and video analysis, applications and services of artificial intelligence and computer vision, interdisciplinary areas combining artificial intelligence and computer vision, and other innovative practices.