File:A Biologically-Inspired Neural Network Architecture for Image Processing (IA abiologicallyins1094530625).pdf
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Summary[edit]
A Biologically-Inspired Neural Network Architecture for Image Processing ( ) | ||
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Author |
Lazofson, Laurence E. |
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Title |
A Biologically-Inspired Neural Network Architecture for Image Processing |
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Description |
This thesis project included a literature survey of biological and artificial neural network research followed by development and testing of high- order and image recognition hierarchical neural network algorithms. Following training, performance testing of second-order and third-order networks yielded maximum accuracies comparable to those achieved by multilayer perceptron classifiers operating on test data sets. Several versions of an image classification algorithm were tested for learning performance using pixel data from forward-looking infrared (FLIR) images of tanks, trucks, target boards, and clutter. Employing the biologically-motivated Lambertization and contrast normalization of pixel windows, correlations with multiple Gabor function wavelets, and a 'phase synchronizing' local averaging routine, the image classification network extracted data features. Different network versions fed the extracted features to varying output classification schemes. To improve separation of problem classes, recommendations were made for varying the parameters of the Gabor function wavelets and modifying the phase synchronization scheme to extract more suitable features from image pixel data. Subjects: |
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Language | English | |
Publication date |
December 1990 publication_date QS:P577,+1990-12-00T00:00:00Z/10 |
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Current location |
IA Collections: navalpostgraduateschoollibrary; fedlink |
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Accession number |
abiologicallyins1094530625 |
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Source | ||
Permission (Reusing this file) |
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Licensing[edit]
Public domainPublic domainfalsefalse |
This work is in the public domain in the United States because it is a work prepared by an officer or employee of the United States Government as part of that person’s official duties under the terms of Title 17, Chapter 1, Section 105 of the US Code.
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This file has been identified as being free of known restrictions under copyright law, including all related and neighboring rights. |
https://creativecommons.org/publicdomain/mark/1.0/PDMCreative Commons Public Domain Mark 1.0falsefalse
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current | 06:32, 8 July 2020 | 1,275 × 1,650, 160 pages (5.52 MB) | Fæ (talk | contribs) | FEDLINK - United States Federal Collection abiologicallyins1094530625 (User talk:Fæ/IA books#Fork8) (batch 1990-1992 #2767) |
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Short title | A Biologically-Inspired Neural Network Architecture for Image Processing |
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Author | Lazofson, Laurence E. |
File change date and time | 03:34, 30 January 2012 |
Date and time of digitizing | 03:34, 30 January 2012 |
Date metadata was last modified | 03:34, 30 January 2012 |
Software used | Lazofson, Laurence E. |
Conversion program | |
Encrypted | no |
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Version of PDF format | 1.4 |