Accession Number : ADA255976


Title :   Neural Nets for Scene Analysis


Descriptive Note : Final rept. 31 Mar 1989-30 Sep 1992,


Corporate Author : CARNEGIE-MELLON UNIV PITTSBURGH PA DEPT OF ELECTRICAL AND COMPUTER ENGINEERING


Personal Author(s) : Casasent, David


Full Text : https://apps.dtic.mil/dtic/tr/fulltext/u2/a255976.pdf


Report Date : Sep 1992


Pagination or Media Count : 60


Abstract : This project involved various new optical and digital neural net techniques for scene analysis. The original neural net concept was the adaptive clustering neural net (ACNN). This is detailed in Chapter 2. Our original associative processor concept was the Ho-Kashyap neural net. This is detailed in Chapter 3. Our overview of how neural nets should be used in scene analysis is detailed in Chapter 4. This also includes an overview of our two new higher order neural nets. Our new PQNN neural net (which produces higher-order decision surfaces much more efficiently than other neural nets) is noted in Chapter 5. To achieve high performance on systems with components with analog accuracy and various nonidealities, we developed a new algorithm and technique discussed in Chapter 6. We have fabricated our optical laboratory neural net and tested it on several different case studies and achieved excellent results as noted in Chapter 7.


Descriptors :   *NEURAL NETS , *OPTICAL DATA , *OPTICAL PROCESSING , ALGORITHMS , DATA PROCESSING , NETS


Subject Categories : Optics


Distribution Statement : APPROVED FOR PUBLIC RELEASE