Brain-Inspired Intelligence and Visual Perception

Brain-Inspired Intelligence and Visual Perception

Author: Wenfeng Wang

Publisher: Springer

Published: 2019-02-14

Total Pages: 166

ISBN-13: 9811335494

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This book presents the latest findings in the field of brain-inspired intelligence and visual perception (BIVP), and discusses novel research assumptions, including an introduction to brain science and the brain vision hypotheses. Moreover, it introduces readers to the theory and algorithms of BIVP – such as pheromone accumulation and iteration, neural cognitive computing mechanisms, the integration and scheduling of core modules, and brain-inspired perception, motion and control – in a step-by-step manner. Accordingly, it will appeal to university researchers, R&D engineers, undergraduate and graduate students; to anyone interested in robots, brain cognition or computer vision; and to all those wishing to learn about the core theory, principles, methods, algorithms, and applications of BIVP.


Brain-Inspired Computing

Brain-Inspired Computing

Author: Katrin Amunts

Publisher: Springer Nature

Published: 2021-07-20

Total Pages: 159

ISBN-13: 3030824276

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This open access book constitutes revised selected papers from the 4th International Workshop on Brain-Inspired Computing, BrainComp 2019, held in Cetraro, Italy, in July 2019. The 11 papers presented in this volume were carefully reviewed and selected for inclusion in this book. They deal with research on brain atlasing, multi-scale models and simulation, HPC and data infra-structures for neuroscience as well as artificial and natural neural architectures.


Exploring Future Opportunities of Brain-Inspired Artificial Intelligence

Exploring Future Opportunities of Brain-Inspired Artificial Intelligence

Author: Bhatia, Madhulika

Publisher: IGI Global

Published: 2023-03-20

Total Pages: 244

ISBN-13: 1668469820

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Applying mechanisms and principles of human intelligence and converging the brain and artificial intelligence (AI) is currently a research trend. The applications of AI in brain simulation are countless. Brain-inspired intelligent systems will improve next-generation information processing by applying theories, techniques, and applications inspired by the information processing principles from the brain. Exploring Future Opportunities of Brain-Inspired Artificial Intelligence focuses on the convergence of AI with brain-inspired intelligence. It presents research on brain-inspired cognitive machines with vision, audition, language processing, and thinking capabilities. Covering topics such as data analysis tools, knowledge representation, and super-resolution, this premier reference source is an essential resource for engineers, developers, computer scientists, students and educators of higher education, librarians, researchers, and academicians.


Visual Intelligence

Visual Intelligence

Author: Donald D Hoffman

Publisher: W. W. Norton & Company

Published: 2000-02-22

Total Pages: 324

ISBN-13: 9780393319675

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In an informal style replete with illustrations, Hoffman presents the compelling scientific evidence for vision's constructive powers unveiling a grammar of vision--a set of rules that govern our perception of line, color, form, depth, and motion. 150 illustrations, 20 in color.


Time-Space, Spiking Neural Networks and Brain-Inspired Artificial Intelligence

Time-Space, Spiking Neural Networks and Brain-Inspired Artificial Intelligence

Author: Nikola K. Kasabov

Publisher: Springer

Published: 2018-08-29

Total Pages: 742

ISBN-13: 3662577151

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Spiking neural networks (SNN) are biologically inspired computational models that represent and process information internally as trains of spikes. This monograph book presents the classical theory and applications of SNN, including original author’s contribution to the area. The book introduces for the first time not only deep learning and deep knowledge representation in the human brain and in brain-inspired SNN, but takes that further to develop new types of AI systems, called in the book brain-inspired AI (BI-AI). BI-AI systems are illustrated on: cognitive brain data, including EEG, fMRI and DTI; audio-visual data; brain-computer interfaces; personalized modelling in bio-neuroinformatics; multisensory streaming data modelling in finance, environment and ecology; data compression; neuromorphic hardware implementation. Future directions, such as the integration of multiple modalities, such as quantum-, molecular- and brain information processing, is presented in the last chapter. The book is a research book for postgraduate students, researchers and practitioners across wider areas, including computer and information sciences, engineering, applied mathematics, bio- and neurosciences.


Biological and Computer Vision

Biological and Computer Vision

Author: Gabriel Kreiman

Publisher: Cambridge University Press

Published: 2021-02-04

Total Pages: 275

ISBN-13: 1108759262

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Imagine a world where machines can see and understand the world the way humans do. Rapid progress in artificial intelligence has led to smartphones that recognize faces, cars that detect pedestrians, and algorithms that suggest diagnoses from clinical images, among many other applications. The success of computer vision is founded on a deep understanding of the neural circuits in the brain responsible for visual processing. This book introduces the neuroscientific study of neuronal computations in visual cortex alongside of the psychological understanding of visual cognition and the burgeoning field of biologically-inspired artificial intelligence. Topics include the neurophysiological investigation of visual cortex, visual illusions, visual disorders, deep convolutional neural networks, machine learning, and generative adversarial networks among others. It is an ideal resource for students and researchers looking to build bridges across different approaches to studying and developing visual systems.


Brain and Visual Perception

Brain and Visual Perception

Author: David H. Hubel M.D.

Publisher: Oxford University Press

Published: 2004-10-14

Total Pages: 739

ISBN-13: 0198039166

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This is the story of a hugely successful and enjoyable 25-year collaboration between two scientists who set out to learn how the brain deals with the signals it receives from the two eyes. Their work opened up a new area of brain research that led to their receiving the Nobel Prize in 1981. The book contains their major papers from 1959 to 1981, each preceded and followed by comments telling how and why the authors went about the study, how the work was received, and what has happened since. It begins with short autobiographies of both men, and describes the state of the field when they started. It is intended not only for neurobiologists, but for anyone interested in how the brain works-biologists, psychologists, philosophers, physicists, historians of science, and students at all levels from high school to graduate level.


Advances in Brain, Vision, and Artificial Intelligence

Advances in Brain, Vision, and Artificial Intelligence

Author: Francesco Mele

Publisher: Springer

Published: 2007-09-21

Total Pages: 632

ISBN-13: 3540755551

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This book constitutes the refereed proceedings of the Second International Symposium on Brain, Vision and Artificial Intelligence, BVAI 2007. Coverage includes: basic models in visual sciences, cortical mechanism of vision, color processing in natural vision, action oriented vision, visual recognition and attentive modulation, biometric recognition, image segmentation and recognition, disparity calculation and noise analysis, meaning-interaction-emotion, and robot navigation.


Interdisciplinary Evolution of the Machine Brain

Interdisciplinary Evolution of the Machine Brain

Author: Wenfeng Wang

Publisher: Springer Nature

Published: 2021-01-04

Total Pages: 154

ISBN-13: 9813342447

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This book seeks to interpret connections between the machine brain, mind and vision in an alternative way and promote future research into the Interdisciplinary Evolution of Machine Brain (IEMB). It gathers novel research on IEMB, and offers readers a step-by-step introduction to the theory and algorithms involved, including data-driven approaches in machine learning, monitoring and understanding visual environments, using process-based perception to expand insights, mechanical manufacturing for remote sensing, reconciled connections between the machine brain, mind and vision, and the interdisciplinary evolution of machine intelligence. This book is intended for researchers, graduate students and engineers in the fields of robotics, Artificial Intelligence and brain science, as well as anyone who wishes to learn the core theory, principles, methods, algorithms, and applications of IEMB.


Neural Information Processing

Neural Information Processing

Author: Bao-Liang Lu

Publisher: Springer

Published: 2011-11-12

Total Pages: 788

ISBN-13: 3642249558

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The three volume set LNCS 7062, LNCS 7063, and LNCS 7064 constitutes the proceedings of the 18th International Conference on Neural Information Processing, ICONIP 2011, held in Shanghai, China, in November 2011. The 262 regular session papers presented were carefully reviewed and selected from numerous submissions. The papers of part I are organized in topical sections on perception, emotion and development, bioinformatics, biologically inspired vision and recognition, bio-medical data analysis, brain signal processing, brain-computer interfaces, brain-like systems, brain-realistic models for learning, memory and embodied cognition, Clifford algebraic neural networks, combining multiple learners, computational advances in bioinformatics, and computational-intelligent human computer interaction. The second volume is structured in topical sections on cybersecurity and data mining workshop, data mining and knowledge doscovery, evolutionary design and optimisation, graphical models, human-originated data analysis and implementation, information retrieval, integrating multiple nature-inspired approaches, kernel methods and support vector machines, and learning and memory. The third volume contains all the contributions connected with multi-agent systems, natural language processing and intelligent Web information processing, neural encoding and decoding, neural network models, neuromorphic hardware and implementations, object recognition, visual perception modelling, and advances in computational intelligence methods based pattern recognition.