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Friday, July 24, 2020 | History

3 edition of NETRA, a parallel architecture for integrated vision systems. found in the catalog.

NETRA, a parallel architecture for integrated vision systems.

Alok N. Choudhary

NETRA, a parallel architecture for integrated vision systems.

by Alok N. Choudhary

  • 143 Want to read
  • 36 Currently reading

Published by Coordinated Science Laboratory, College of Engineering, University of Illinois at Urbana-Champaign in [Urbana, Ill.] .
Written in English

    Subjects:
  • Algorithms.,
  • Architecture (Computers),
  • Computer vision.,
  • Image processing.,
  • Multiprocessing (Computers),
  • Parallel processing (Computers),
  • Performance tests.

  • Edition Notes

    StatementAlok N. Choudhary, Janak H. Patel, Narendra Ahuja.
    SeriesNASA contractor report -- NASA CR-186510.
    ContributionsPatel, Janak H., 1948-, Ahuja, Narendra, 1950-, University of Illinois at Urbana-Champaign. Coordinated Science Laboratory., United States. National Aeronautics and Space Administration.
    The Physical Object
    FormatMicroform
    Pagination1 v.
    ID Numbers
    Open LibraryOL16137994M

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NETRA, a parallel architecture for integrated vision systems by Alok N. Choudhary Download PDF EPUB FB2

Get this from a library. NETRA, a parallel architecture for integrated vision systems. I, Architecture and organization. [Alok N Choudhary; Janak H Patel; Narendra Ahuja; United States. National Aeronautics and Space Administration.; University of Illinois at Urbana-Champaign.

Coordinated Science Laboratory.]. Get this from a library. NETRA, a parallel architecture for integrated vision systems. II, Algorithms and performance evaluation. [Alok N Choudhary; Janak H Patel; Narendra Ahuja; University of Illinois at Urbana-Champaign.

Coordinated Science Laboratory.; United States. National Aeronautics and Space Administration.]. Choudhary A.N., Patel J.H.

() Architecture NETRA NETRA. In: Parallel Architectures and Parallel Algorithms for Integrated Vision Systems. The Kluwer International Series in Engineering and Computer Science (Robotics: Vision, Manipulation and Sensors), vol Author: Alok N.

Choudhary, Janak H. Patel. Specifically, algorithms from low level vision that involve computations closely mimicking the architec­ ture and require simple control and computations are suitable for massively parallel SIMD computers.

An Integrated Vision System (IVS) involves com­ putations from low to high level vision to be executed in a systematic fashion and repeatedly. Several parallel vision algorithms have been designed for this architecture. The choice of vision problems demonstrates the versatility of ACMAA for a wide range of vision : Michael Bolotski.

We use cookies to offer you a better experience, personalize content, tailor advertising, provide social media features, and better understand the use of our services. Alok Choudhary and Janak Patel. Performance of Integrated Image Understanding Benchmarks on NETRA: A Parallel Architecture for Integrated Vision Systems.

In the DARPA Image Understanding Benchmark Workshop, October (pdf unavailable) Poster. A parallel of the antient architecture with the modern in a collection of ten principal authors who a parallel architecture for integrated vision systems. book written upon the five orders, viz. Palladio and Scamozzi, Serlio and Vignola, D.

Barbaro and Cataneo, L. Alberti and Viola, Bullant and D Lorme, compared with one another. Ahuja, Issues in the Design of Integrated Vision Systems, Int. Joint Conference on Artificial Intelligence Workshop W-7, Sydney, Australia, AugPart III.

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This paper presents a bibliography of over references related to computer vision and image analysis, arranged by subject matter.

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Computer Vision Systems (), pp. – A one‐pass thinning algorithm and its parallel implementation. Computer Vision, Graphics, and Image Process 1 (), pp. 30 – Crossref Web of Science ® Wiley Online Library CAS PubMed Web of Science. Ahuja and M. Tabb, Multiscale Image Edge and Region Detection Method and Apparatus, U.

Patent, Issued September R. Dugad and N. Ahuja, Transform Domain Significant Coefficient Digital Image Watermarking Method, U.S.

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