Application of neural networks to pattern recognition problems in remote sensing and medical imagery

Jo Ann Parikh; John S. DaPonte; Meledath Damodaran; Porter Sherman

doi:10.1117/12.21165

1 August 1990 Application of neural networks to pattern recognition problems in remote sensing and medical imagery

Jo Ann Parikh, John S. DaPonte, Meledath Damodaran, Porter Sherman

Proceedings Volume 1294, Applications of Artificial Neural Networks; (1990) https://doi.org/10.1117/12.21165
Event: 1990 Technical Symposium on Optics, Electro-Optics, and Sensors, 1990, Orlando, FL, United States

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.

Citation Download Citation

Jo Ann Parikh, John S. DaPonte, Meledath Damodaran, and Porter Sherman "Application of neural networks to pattern recognition problems in remote sensing and medical imagery", Proc. SPIE 1294, Applications of Artificial Neural Networks, (1 August 1990); https://doi.org/10.1117/12.21165

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