Neural Nets for Scene Analysis
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.
Document Details
- Document Type
- Technical Report
- Publication Date
- Sep 01, 1992
- Accession Number
- ADA255976
Entities
People
- David P. Casasent
Organizations
- Carnegie Mellon University