Title :
A neuro-expert architecture for object recognition
Author :
Selinsky, John ; Guez, Allon ; Eilbert, James ; Kam, Moshe
Author_Institution :
Dept. of Electr. & Comput. Eng., Drexel Univ., Philadelphia, PA, USA
Abstract :
Summary form only given, as follows. A report is presented on results of experiments in object recognition with a combined neural network/expert system architecture (neuro-expert). The neuro-expert architecture is outlined with a description of the experimental object recognition system. Results are reported for the recognition of a 20-pattern prototype set of synthesized binary images placed at arbitrary rotations. A 100% recognition rate was obtained under noiseless conditions. Addition of 1% and 2% random pixel noise resulted in recognition rates of 95.2% and 89.5%, respectively.<>
Keywords :
computerised pattern recognition; expert systems; neural nets; parallel architectures; random noise; 20-pattern prototype set; arbitrary rotations; expert system; neural network; neuro-expert architecture; noiseless conditions; object recognition; random pixel noise; recognition rate; synthesized binary images; Expert systems; Neural networks; Parallel architectures; Pattern recognition; Random noise;
Conference_Titel :
Neural Networks, 1989. IJCNN., International Joint Conference on
Conference_Location :
Washington, DC, USA
DOI :
10.1109/IJCNN.1989.118315
