Neural Nets for Scene Analysis
Final rept. 31 Mar 1989-30 Sep 1992,
CARNEGIE-MELLON UNIV PITTSBURGH PA DEPT OF ELECTRICAL AND COMPUTER ENGINEERING
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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.