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Proceedings Paper

Application of neural networks to pattern recognition problems in remote sensing and medical imagery
Author(s): Jo Ann Parikh; John S. DaPonte; Meledath Damodaran; Porter Sherman
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Paper Abstract

The primary objective of this research is the development and testing of neural network models for two fundamental computer vision tasks: edge/line detection and texture analysis. In order to test the ability of the neural network models to detect patterns in images we used both remote sensing data and medical imagery. Neural network models for edge and line detection were used to detect geological lineaments in Landsat data. Neural network models for the analysis of image texture variations were used on ultrasonic images to distinguish patients with normal liver scans from patients with diffuse liver disease. 1.

Paper Details

Date Published: 1 August 1990
PDF: 15 pages
Proc. SPIE 1294, Applications of Artificial Neural Networks, (1 August 1990); doi: 10.1117/12.21165
Show Author Affiliations
Jo Ann Parikh, Southern Connecticut State Univ. (United States)
John S. DaPonte, Southern Connecticut State Univ. (United States)
Meledath Damodaran, Univ. of Bridgeport (United States)
Porter Sherman, Univ. of Bridgeport (United States)

Published in SPIE Proceedings Vol. 1294:
Applications of Artificial Neural Networks
Steven K. Rogers, Editor(s)

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