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Author: Jeanny Hrault
Publisher: World Scientific
ISBN: 9814273694
Category : Computers
Languages : en
Pages : 308
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Book Description
At the fascinating frontiers of neurobiology, mathematics and psychophysics, this book addresses the problem of human and computer vision on the basis of cognitive modeling. After recalling the physics of light and its transformation through media and optics, Hrault presents the principles of the primate's visual system in terms of anatomy and functionality. Then, the neuronal circuitry of the retina is analyzed in terms of spatio?temporal filtering. This basic model is extended to the concept of neuromorphic circuits for motion processing and to the processing of color in the retina. For more in-depth studies, the adaptive non-linear properties of the photoreceptors and of ganglion cells are addressed, exhibiting all the power of the retinal pre-processing of images as a system of information cleaning suitable for further cortical processing. As a target of retinal information, the primary visual area is presented as a bank of filters able to extract valuable descriptors of images, suitable for categorization and recognition and also for local information extraction such as saliency and perspective. All along the book, many comparisons between the models and human perception are discussed as well as detailed applications to computer vision.
Author: Jeanny Hrault
Publisher: World Scientific
ISBN: 9814273694
Category : Computers
Languages : en
Pages : 308
Get Book Here
Book Description
At the fascinating frontiers of neurobiology, mathematics and psychophysics, this book addresses the problem of human and computer vision on the basis of cognitive modeling. After recalling the physics of light and its transformation through media and optics, Hrault presents the principles of the primate's visual system in terms of anatomy and functionality. Then, the neuronal circuitry of the retina is analyzed in terms of spatio?temporal filtering. This basic model is extended to the concept of neuromorphic circuits for motion processing and to the processing of color in the retina. For more in-depth studies, the adaptive non-linear properties of the photoreceptors and of ganglion cells are addressed, exhibiting all the power of the retinal pre-processing of images as a system of information cleaning suitable for further cortical processing. As a target of retinal information, the primary visual area is presented as a bank of filters able to extract valuable descriptors of images, suitable for categorization and recognition and also for local information extraction such as saliency and perspective. All along the book, many comparisons between the models and human perception are discussed as well as detailed applications to computer vision.
Author: Gail A. Carpenter
Publisher: Springer Science & Business
ISBN: 9780262531085
Category : Computers
Languages : en
Pages : 492
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Book Description
This interdisciplinary survey brings together recent models and experiments on how the brain sees and learns to recognize objects. It shows how to use these insights in technology and describes how neural networks provide a unifying computational framework for reaching these goals. Several chapters describe experiments in neurobiology and visual perception that clarify properties of biological vision and key conceptual issues that biological models need to address. Other chapters describe neural and computational models of biological vision that address such issues and clarify processes whereby biological vision derives its remarkable flexibility and power. Still other chapters use biologically derived models or heuristics to suggest neural network solutions to challenging technological problems in computer vision. Topics range from analyses of motion, depth, color and form to new concepts about learning, attention, pattern recognition, and hardware implementation.
Author: Roumen Kountchev
Publisher: Springer Science & Business Media
ISBN: 3642246931
Category : Technology & Engineering
Languages : en
Pages : 460
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Book Description
The book puts special stress on the contemporary techniques for reasoning-based image processing and analysis: learning based image representation and advanced video coding; intelligent image processing and analysis in medical vision systems; similarity learning models for image reconstruction; visual perception for mobile robot motion control, simulation of human brain activity in the analysis of video sequences; shape-based invariant features extraction; essential of paraconsistent neural networks, creativity and intelligent representation in computational systems. The book comprises 14 chapters. Each chapter is a small monograph, representing resent investigations of authors in the area. The topics of the chapters cover wide scientific and application areas and complement each-other very well. The chapters’ content is based on fundamental theoretical presentations, followed by experimental results and comparison with similar techniques. The size of the chapters is well-ballanced which permits a thorough presentation of the investigated problems. The authors are from universities and R&D institutions all over the world; some of the chapters are prepared by international teams. The book will be of use for university and PhD students, researchers and software developers working in the area of digital image and video processing and analysis.
Author: Harry Wechsler
Publisher: Academic Press
ISBN: 1483260259
Category : Computers
Languages : en
Pages : 543
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Book Description
Neural Networks for Perception, Volume 1: Human and Machine Perception focuses on models for understanding human perception in terms of distributed computation and examples of PDP models for machine perception. This book addresses both theoretical and practical issues related to the feasibility of both explaining human perception and implementing machine perception in terms of neural network models. The book is organized into two parts. The first part focuses on human perception. Topics on network model of object recognition in human vision, the self-organization of functional architecture in the cerebral cortex, and the structure and interpretation of neuronal codes in the visual system are detailed under this part. Part two covers the relevance of neural networks for machine perception. Subjects considered under this section include the multi-dimensional linear lattice for Fourier and Gabor transforms, multiple- scale Gaussian filtering, and edge detection; aspects of invariant pattern and object recognition; and neural network for motion processing. Neuroscientists, computer scientists, engineers, and researchers in artificial intelligence will find the book useful.
Author: Sven Behnke
Publisher: Springer Science & Business Media
ISBN: 3540407227
Category : Computers
Languages : en
Pages : 230
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Book Description
Human performance in visual perception by far exceeds the performance of contemporary computer vision systems. While humans are able to perceive their environment almost instantly and reliably under a wide range of conditions, computer vision systems work well only under controlled conditions in limited domains. This book sets out to reproduce the robustness and speed of human perception by proposing a hierarchical neural network architecture for iterative image interpretation. The proposed architecture can be trained using unsupervised and supervised learning techniques. Applications of the proposed architecture are illustrated using small networks. Furthermore, several larger networks were trained to perform various nontrivial computer vision tasks.
Author: Bogdan Ionescu
Publisher: Springer Nature
ISBN: 3030814653
Category : Computers
Languages : en
Pages : 297
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Book Description
Recent years have witnessed important advancements in our understanding of the psychological underpinnings of subjective properties of visual information, such as aesthetics, memorability, or induced emotions. Concurrently, computational models of objective visual properties such as semantic labelling and geometric relationships have made significant breakthroughs using the latest achievements in machine learning and large-scale data collection. There has also been limited but important work exploiting these breakthroughs to improve computational modelling of subjective visual properties. The time is ripe to explore how advances in both of these fields of study can be mutually enriching and lead to further progress. This book combines perspectives from psychology and machine learning to showcase a new, unified understanding of how images and videos influence high-level visual perception - particularly interestingness, affective values and emotions, aesthetic values, memorability, novelty, complexity, visual composition and stylistic attributes, and creativity. These human-based metrics are interesting for a very broad range of current applications, ranging from content retrieval and search, storytelling, to targeted advertising, education and learning, and content filtering. Work already exists in the literature that studies the psychological aspects of these notions or investigates potential correlations between two or more of these human concepts. Attempts at building computational models capable of predicting such notions can also be found, using state-of-the-art machine learning techniques. Nevertheless their performance proves that there is still room for improvement, as the tasks are by nature highly challenging and multifaceted, requiring thought on both the psychological implications of the human concepts, as well as their translation to machines.
Author: V. Cantoni
Publisher:
ISBN:
Category : Business & Economics
Languages : en
Pages : 424
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Book Description
The phylogenetic evolution of the visual system. A control view to vision architectures. Panel summary - one model for vision systems? Structure and function in the retina. On-chip vision. Panel summary - foveation, log-polar mapping and multiscale approaches to early vision. Neurophysiology of the striate cortex. Visual form representation. Panel summary - looking for visual primitives. The oculomotor system. Active vision. Panel summary - allocation of attention in vision. New wine in old barrels: knowing how to move tells us how to perceive movement. Motion analysis. Pannel summary - dynamic perception of the environment. Visual cognition and cognitive modeling. Models and descriptions in machine vision. Panel summary - icons and words: metaphors and symbolisms. Visual thinking: stability and self-organisation. Spatial reasoning as a tool for scene generation and recognition. Panel summary - image interpretation and ambiguities. From imagery to imagination. Neural networks, fuzziness and image processing. Panel summary - perceptual learning and discovering. The state of the art in virtual reality.
Author: Věra Kůrková
Publisher: Springer
ISBN: 3030014215
Category : Computers
Languages : en
Pages : 632
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Book Description
This three-volume set LNCS 11139-11141 constitutes the refereed proceedings of the 27th International Conference on Artificial Neural Networks, ICANN 2018, held in Rhodes, Greece, in October 2018. The 139 full and 28 short papers as well as 41 full poster papers and 41 short poster papers presented in these volumes was carefully reviewed and selected from total of 360 submissions. They are related to the following thematic topics: AI and Bioinformatics, Bayesian and Echo State Networks, Brain Inspired Computing, Chaotic Complex Models, Clustering, Mining, Exploratory Analysis, Coding Architectures, Complex Firing Patterns, Convolutional Neural Networks, Deep Learning (DL), DL in Real Time Systems, DL and Big Data Analytics, DL and Big Data, DL and Forensics, DL and Cybersecurity, DL and Social Networks, Evolving Systems – Optimization, Extreme Learning Machines, From Neurons to Neuromorphism, From Sensation to Perception, From Single Neurons to Networks, Fuzzy Modeling, Hierarchical ANN, Inference and Recognition, Information and Optimization, Interacting with The Brain, Machine Learning (ML), ML for Bio Medical systems, ML and Video-Image Processing, ML and Forensics, ML and Cybersecurity, ML and Social Media, ML in Engineering, Movement and Motion Detection, Multilayer Perceptrons and Kernel Networks, Natural Language, Object and Face Recognition, Recurrent Neural Networks and Reservoir Computing, Reinforcement Learning, Reservoir Computing, Self-Organizing Maps, Spiking Dynamics/Spiking ANN, Support Vector Machines, Swarm Intelligence and Decision-Making, Text Mining, Theoretical Neural Computation, Time Series and Forecasting, Training and Learning.
Author: Lothar Spillmann
Publisher: Elsevier
ISBN: 0323138144
Category : Psychology
Languages : en
Pages : 550
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Book Description
This book presents an interdisciplinary overview of the main facts and theories that guide contemporary research on visual perception. While the chapters cover virtually all areas of visual science, from philosophical foundations to computational algorithms, and from photoreceptor processes to neuronal networks, no attempt has been made to provide an exhaustive treatment of these topics. Rather, researchers from such diverse disciplines as psychology, neurophysiology, anatomy, and clinical vision sciences have worked together to review some of the most important correlations between perceptual phenomena and the underlying neurophysiological processes and mechanisms. The book is thus intended to serve as an advanced text for graduate students and as a guide for all vision researchers to understanding current progress outside their specialized fields of interest. ï Examines parallel processing of visual informationï Discusses links between physiologically-measured receptive fields and psychophysically-measured perceptive fieldsï Presents a spatial sampling by the retina and cortical modulesï Covers signal transduction and the sites of adaptationï Describes a single-cell analysis of attentionï Discusses computational models of vision
Author: Gabriel Cristobal
Publisher: John Wiley & Sons
ISBN: 3527680470
Category : Technology & Engineering
Languages : en
Pages : 482
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Book Description
As the state-of-the-art imaging technologies became more and more advanced, yielding scientific data at unprecedented detail and volume, the need to process and interpret all the data has made image processing and computer vision increasingly important. Sources of data that have to be routinely dealt with today's applications include video transmission, wireless communication, automatic fingerprint processing, massive databanks, non-weary and accurate automatic airport screening, robust night vision, just to name a few. Multidisciplinary inputs from other disciplines such as physics, computational neuroscience, cognitive science, mathematics, and biology will have a fundamental impact in the progress of imaging and vision sciences. One of the advantages of the study of biological organisms is to devise very different type of computational paradigms by implementing a neural network with a high degree of local connectivity. This is a comprehensive and rigorous reference in the area of biologically motivated vision sensors. The study of biologically visual systems can be considered as a two way avenue. On the one hand, biological organisms can provide a source of inspiration for new computational efficient and robust vision models and on the other hand machine vision approaches can provide new insights for understanding biological visual systems. Along the different chapters, this book covers a wide range of topics from fundamental to more specialized topics, including visual analysis based on a computational level, hardware implementation, and the design of new more advanced vision sensors. The last two sections of the book provide an overview of a few representative applications and current state of the art of the research in this area. This makes it a valuable book for graduate, Master, PhD students and also researchers in the field.
