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.
This book provides detailed practical guidelines on how to develop an efficient pathological brain detection system, reflecting the latest advances in the computer-aided diagnosis of structural magnetic resonance brain images.
The thirty original contributions in this book provide a working definition of"computational neuroscience" as the area in which problems lie simultaneously within computerscience and neuroscience.
NETMORPH: a framework for the stochastic generation of large scale neuronal networks with realistic neuron morphologies. ... in Progress in Brain Research, The Self-Organizing Brain: From Growth Cones to Functional Networks, Vol.
The annual Computational Neuroscience Meeting (CNS) began in 1990 as a small workshop called Analysis and Modeling of Neural Systems. The goal of the workshop was to explore the boundary between neuroscience and computation.
A key figure in this exciting development is the logician and mathematician Helmut Schwichtenberg to whom this volume is dedicated on the occasion of his 70th birthday and his turning emeritus.
This book describes the algorithms and architectures that are driving progress in AI research in this language, by comparing current AI systems and biological brains side by side.
This thesis work consists in a theoretical and computational study of a recently-indentified type of synaptic plasticity, called "spike-timing dependent plasticity" (STDP).