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Depth Perception in Frogs and Toads

A Study in Neural Computing

  • Book
  • © 1989

Overview

Part of the book series: Lecture Notes in Biomathematics (LNBM, volume 80)

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Table of contents (6 chapters)

Keywords

About this book

Depth Perception in Frogs and Toads provides a comprehensive exploration of the phenomenon of depth perception in frogs and toads, as seen from a neuro-computational point of view. Perhaps the most important feature of the book is the development and presentation of two neurally realizable depth perception algorithms that utilize both monocular and binocular depth cues in a cooperative fashion. One of these algorithms is specialized for computation of depth maps for navigation, and the other for the selection and localization of a single prey for prey catching. The book is also unique in that it thoroughly reviews the known neuroanatomical, neurophysiological and behavioral data, and then synthesizes, organizes and interprets that information to explain a complex sensory-motor task. The book will be of special interest to that segment of the neural computing community interested in understanding natural neurocomputational structures, particularly to those working in perception and sensory-motor coordination. It will also be of interest to neuroscientists interested in exploring the complex interactions between the neural substrates that underly perception and behavior.

Authors and Affiliations

  • Department of Computer Science, Williams College, Williamstown, USA

    Donald House

Bibliographic Information

  • Book Title: Depth Perception in Frogs and Toads

  • Book Subtitle: A Study in Neural Computing

  • Authors: Donald House

  • Series Title: Lecture Notes in Biomathematics

  • DOI: https://doi.org/10.1007/978-1-4684-6391-0

  • Publisher: Springer New York, NY

  • eBook Packages: Springer Book Archive

  • Copyright Information: Springer-Verlag New York, Inc. 1989

  • Softcover ISBN: 978-0-387-97157-5Published: 22 November 1989

  • eBook ISBN: 978-1-4684-6391-0Published: 13 March 2013

  • Series ISSN: 0341-633X

  • Series E-ISSN: 2196-9981

  • Edition Number: 1

  • Number of Pages: VII, 135

  • Topics: Neurosciences, Mathematical and Computational Biology, Artificial Intelligence

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