DocumentCode
330314
Title
Application of neural networks in detecting hyperellipsoidal shells
Author
Su, Mu-Chun ; Liu, I-Chen
Author_Institution
Dept. of Electr. Eng., Tamkang Univ., Tamsui, Taiwan
Volume
2
fYear
1998
fDate
11-14 Oct 1998
Firstpage
1779
Abstract
This paper presents a novel class of neural networks which can be trained in an unsupervised manner to detect a mixture of hyperellipsoidal shells and/or segment of hyperellipsoidal shells. This approach is computationally and implementationally simpler than other clustering algorithms that have been suggested for this purpose. Experimental results are given to show the effectiveness of the proposed method
Keywords
computational complexity; image recognition; neural nets; pattern clustering; unsupervised learning; clustering algorithms; computational complexity; hyperellipsoidal shell detection; neural networks; unsupervised training; Automatic frequency control; Clustering algorithms; Clustering methods; Computer vision; Digital images; Electronic mail; Extraterrestrial measurements; Intelligent networks; Neural networks; Shape measurement;
fLanguage
English
Publisher
ieee
Conference_Titel
Systems, Man, and Cybernetics, 1998. 1998 IEEE International Conference on
Conference_Location
San Diego, CA
ISSN
1062-922X
Print_ISBN
0-7803-4778-1
Type
conf
DOI
10.1109/ICSMC.1998.728152
Filename
728152
Link To Document