ROCIT : a visual object recognition algorithm based on a rank-order coding scheme.

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This document describes ROCIT, a neural-inspired object recognition algorithm based on a rank-order coding scheme that uses a light-weight neuron model. ROCIT coarsely simulates a subset of the human ventral visual stream from the retina through the inferior temporal cortex. It was designed to provide an extensible baseline from which to improve the fidelity of the ventral stream model and explore the engineering potential of rank order coding with respect to object recognition. This report describes the baseline algorithm, the model's neural network architecture, the theoretical basis for the approach, and reviews the history of similar implementations. Illustrative results are ... continued below

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80 p.

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Gonzales, Antonio Ignacio; Reeves, Paul C.; Jones, John J. & Farkas, Benjamin D. June 1, 2004.

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This report is part of the collection entitled: Office of Scientific & Technical Information Technical Reports and was provided by UNT Libraries Government Documents Department to Digital Library, a digital repository hosted by the UNT Libraries. It has been viewed 54 times , with 7 in the last month . More information about this report can be viewed below.

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Description

This document describes ROCIT, a neural-inspired object recognition algorithm based on a rank-order coding scheme that uses a light-weight neuron model. ROCIT coarsely simulates a subset of the human ventral visual stream from the retina through the inferior temporal cortex. It was designed to provide an extensible baseline from which to improve the fidelity of the ventral stream model and explore the engineering potential of rank order coding with respect to object recognition. This report describes the baseline algorithm, the model's neural network architecture, the theoretical basis for the approach, and reviews the history of similar implementations. Illustrative results are used to clarify algorithm details. A formal benchmark to the 1998 FERET fafc test shows above average performance, which is encouraging. The report concludes with a brief review of potential algorithmic extensions for obtaining scale and rotational invariance.

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80 p.

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  • Report No.: SAND2004-2129
  • Grant Number: AC04-94AL85000
  • DOI: 10.2172/919190 | External Link
  • Office of Scientific & Technical Information Report Number: 919190
  • Archival Resource Key: ark:/67531/metadc890306

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Office of Scientific & Technical Information Technical Reports

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Creation Date

  • June 1, 2004

Added to The UNT Digital Library

  • Sept. 22, 2016, 2:13 a.m.

Description Last Updated

  • Dec. 8, 2016, 9:18 p.m.

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Gonzales, Antonio Ignacio; Reeves, Paul C.; Jones, John J. & Farkas, Benjamin D. ROCIT : a visual object recognition algorithm based on a rank-order coding scheme., report, June 1, 2004; United States. (digital.library.unt.edu/ark:/67531/metadc890306/: accessed November 17, 2018), University of North Texas Libraries, Digital Library, digital.library.unt.edu; crediting UNT Libraries Government Documents Department.