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Vision science has grown hugely in the past decades, but there have been few books showing readers how to adopt a computional approach to understanding visual perception, along with the underlying mechanisms in the brain. This book explains the computational principles and models of biological visual processing, and in particular, primate vision.
While the field of vision science has grown significantly in the past three decades, there have been few comprehensive books that showed readers how to adopt a computional approach to understanding visual perception, along with the underlying mechanisms in the brain. Understanding Vision explains the computational principles and models of biological visual processing, and in particular, of primate vision. The book is written in such a way that vision scientists, unfamiliar with mathematical details, should be able to conceptually follow the theoretical principles and their relationship with physiological, anatomical, and psychological observations, without going through the more mathematical...
The refereed proceedings of the Joint International Conference on Artificial Neural Networks and International Conference on Neural Information Processing, ICANN/ICONIP 2003, held in Istanbul, Turkey, in June 2003. The 138 revised full papers were carefully reviewed and selected from 346 submissions. The papers are organized in topical sections on learning algorithms, support vector machine and kernel methods, statistical data analysis, pattern recognition, vision, speech recognition, robotics and control, signal processing, time-series prediction, intelligent systems, neural network hardware, cognitive science, computational neuroscience, context aware systems, complex-valued neural networks, emotion recognition, and applications in bioinformatics.
Since the appearance of Vol. 1 of Models of Neural Networks in 1991, the theory of neural nets has focused on two paradigms: information coding through coherent firing of the neurons and functional feedback. Information coding through coherent neuronal firing exploits time as a cardinal degree of freedom. This capacity of a neural network rests on the fact that the neuronal action potential is a short, say 1 ms, spike, localized in space and time. Spatial as well as temporal correlations of activity may represent different states of a network. In particular, temporal correlations of activity may express that neurons process the same "object" of, for example, a visual scene by spiking at the ...
Proceedings of the Fifth International School on Neural Networks "E.R. Caianiello" on Visual Attention MechaProceedings of the Fifth International School on Neural Networks "E.R. Caianiello" on Visual Attention Mechanisms, held 23-28 October 2000 in Vietri sul Mare, Italy.nisms, held 23-28 October 2000 in Vietri sul Mare, Italy. The book covers a number of broad themes relevant to visual attention, ranging from computer vision to psychology and physiology of vision. The main theme of the book is the attention processes of vision systems and it aims to point out the analogies and the divergences of biological vision with the frameworks introduced by computer scientists in artificial vision.
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.
This volume includes papers presented at the Third Annual Computation and Neural Systems meeting (CNS*94) held in Monterey California, July 21 - July 26, 1994. This collection includes 71 of the more than 100 papers presented at this year's meeting. Acceptance for meeting presentation was based on the peer review of preliminary papers by at least two referees. The papers in this volume were submitted in final form after the meeting. As represented by this volume, CNS meetings continue to expand in quality, size and breadth of focus as increasing numbers of neuroscientists are taking a computational approach to understanding nervous system function. The CNS meetings are intended to showcase t...
Computational neuroscience is best defined by its focus on understanding the nervous systems as a computational device rather than by a particular experimental technique. Accordinlgy, while the majority of the papers in this book describe analysis and modeling efforts, other papers describe the results of new biological experiments explicitly placed in the context of computational issues. The distribution of subjects in Computation and Neural Systems reflects the current state of the field. In addition to the scientific results presented here, numerous papers also describe the ongoing technical developments that are critical for the continued growth of computational neuroscience. Computation and Neural Systems includes papers presented at the First Annual Computation and Neural Systems meeting held in San Francisco, CA, July 26--29, 1992.
This title includes a number of Open Access chapters.This new book presents a variety of important research on functional foods-foods that have another role related to disease prevention or health. The first section of the book includes chapters on the complicated relationships between nutrition, physical and mental health, and disease. Section&nbs
This book can change the way you think. Literally. “This informative, accessible cookbook will be a boon to health-conscious eaters.” —Publishers Weekly If you struggle with focus and memory lapses, mental fog, or stress—or if you simply want to optimize your mental performance and protect your brain health—Smart Plants is a must read. Written by New York Times bestselling author and natural-food chef Julie Morris, whose name has become synonymous with “superfoods” and “wellness,” this groundbreaking book reveals the dietary secrets to better brain performance. Combining scientific research with the wisdom of ancient remedies, Smart Plants showcases an exciting array of cognition-enhancing plants—from everyday foods to natural nootropics (edibles that can improve memory, learning, and problem solving). Morris’s 65 mouthwatering, beautifully illustrated recipes make it easy to incorporate these powerful foods into your daily diet. Feed your brain with such palate-pleasing dishes as Berry-Almond Amaranth Porridge, French Lentils with Roasted Radishes, Fig & Hazelnut Wild Rice Salad, Garlicky Butter Bean Soup with Kale, Matcha Custard with Wild Berries, and more!