DocumentCode
2945007
Title
Hybrid AI system for geometric pattern recognition
Author
Fernando, Christopher G. ; Munasinghe, Ranjith
Author_Institution
Dept. of Ind. Technol., West Virginia Univ. Inst. of Technol., Montgomery, WV, USA
fYear
2004
fDate
2004
Firstpage
128
Lastpage
131
Abstract
The research area of hybrid and neural processing has been actively developing. Hybrid neural systems are computational systems which are based mainly on artificial neural networks but also allow a symbolic interpretation or interaction with symbolic classical artificial intelligence. In this paper we describe a hybrid AI system developed for 2D object recognition. The 2D object recognition system was developed as the initial step for developing a 3D object recognition system for an unmanned aerial vehicle (UAV).
Keywords
artificial intelligence; computer vision; neural nets; object recognition; remotely operated vehicles; 2D object recognition; artificial intelligence; artificial neural networks; computational systems; geometric pattern recognition; hybrid AI system; hybrid neural systems; symbolic interpretation; unmanned aerial vehicle; Artificial intelligence; Artificial neural networks; Biological neural networks; Computer networks; Expert systems; Humans; Neurons; Object recognition; Pattern recognition; Robustness;
fLanguage
English
Publisher
ieee
Conference_Titel
System Theory, 2004. Proceedings of the Thirty-Sixth Southeastern Symposium on
ISSN
0094-2898
Print_ISBN
0-7803-8281-1
Type
conf
DOI
10.1109/SSST.2004.1295633
Filename
1295633
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