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Parallel Algorithms for Machine Intelligence and Vision

  • Book
  • © 1990

Overview

Editors:
  1. Vipin Kumar

    1. Computer Science Department, University of Minnesota, Minneapolis, USA

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  2. P. S. Gopalakrishnan

    1. IBM T.J. Watson Research Center, Yorktown Heights, USA

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  3. Laveen N. Kanal

    1. LNK Corporation, Riverdale, USA

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Part of the book series: Symbolic Computation (SYMBOLIC)

Part of the book sub series: Artificial Intelligence (1064)

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Table of contents (12 chapters)

  1. Front Matter

    Pages i-xi
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  2. Scalable Parallel Formulations of Depth-First Search

    • Vipin Kumar, V. Nageshwara Rao
    Pages 1-41

  3. Parallel Heuristic Search: Two Approaches

    • Curt Powley, Chris Ferguson, Richard E. Korf
    Pages 42-65

  4. Distributed Game Tree Search

    • R. Feldmann, B. Monien, P. Mysliwietz, O. Vornberger
    Pages 66-101

  5. Multiprocessing of Combinatorial Search Problems

    • Benjamin W. Wah, Guo-Jie Li, Chee-Fen Yu
    Pages 102-145

  6. Parallel Problem Solving

    • L. V. Kaié
    Pages 146-181

  7. Prism: a Testbed for Parallel Control

    • Mark E. Giuliano, Madhur Kohli, Jack Minker, Irene Durand
    Pages 182-231

  8. Or-Parallelism in Natural Language Parsing

    • William C. Hopkins, Lynette Hirschman, Robert C. Smith
    Pages 232-270

  9. Parallelism in Computer Vision: a Review

    • Vipin Chaudhary, J. K. Aggarwal
    Pages 271-309

  10. Real-Time, Parallel Motion Tracking of Three Dimensional Objects From Spatiotemporal Sequences

    • Gilbert Verghese, Karey Lynch Gale, Charles R. Dyer
    Pages 310-339

  11. Parallel Simulation of a Connectionist Stereo Algorithm on a Shared-Memory Multiprocessor

    • Charles V. Stewart, Charles R. Dyer
    Pages 340-359

  12. Parallel Algorithms for Image Template Matching

    • Sanjay Ranka, Sartaj Sahni
    Pages 360-399

  13. Image Computations on Fine Grain Electro-Optical Arrays

    • Mehrnoosh Mary Eshaghian, V. K. Prasanna Kumar
    Pages 400-423

  14. Back Matter

    Pages 425-435
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Keywords

About this book

Recent research results in the area of parallel algorithms for problem solving, search, natural language parsing, and computer vision, are brought together in this book. The research reported demonstrates that substantial parallelism can be exploited in various machine intelligence and vision problems. The chapter authors are prominent researchers actively involved in the study of parallel algorithms for machine intelligence and vision. Extensive experimental studies are presented that will help the reader in assessing the usefulness of an approach to a specific problem. Intended for students and researchers actively involved in parallel algorithms design and in machine intelligence and vision, this book will serve as a valuable reference work as well as an introduction to several research directions in these areas.

Editors and Affiliations

  • Computer Science Department, University of Minnesota, Minneapolis, USA

    Vipin Kumar

  • IBM T.J. Watson Research Center, Yorktown Heights, USA

    P. S. Gopalakrishnan

  • LNK Corporation, Riverdale, USA

    Laveen N. Kanal

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