Share Email Print
cover

Proceedings Paper

Hybrid architecture for KIMS object recognition in a multicontext scene
Author(s): Celestine A. Ntuen; Evi H. Park; Jung H. Kim; Shiu M. Cheung
Format Member Price Non-Member Price
PDF $14.40 $18.00

Paper Abstract

In a multicontext scene where several objects may be occluded or scenes may change rapidly, a single paradigm for computer vision may not be sufficient. The demand to adjust and learn new environment is therefore a challenging modeling problem in computer vision research. In response to this challenge we have developed a hybrid architecture which combines classical pattern recognition algorithms with fuzzy knowledge-base and Hopfield Neural Network. We also present elementary results obtained from this effort.

Paper Details

Date Published: 1 February 1994
PDF: 9 pages
Proc. SPIE 2093, Substance Identification Analytics, (1 February 1994); doi: 10.1117/12.172537
Show Author Affiliations
Celestine A. Ntuen, North Carolina A&T State Univ. (United States)
Evi H. Park, North Carolina A&T State Univ. (United States)
Jung H. Kim, North Carolina A&T State Univ. (United States)
Shiu M. Cheung, FAA Technical Ctr. (United States)


Published in SPIE Proceedings Vol. 2093:
Substance Identification Analytics

© SPIE. Terms of Use
Back to Top