DocumentCode
1407142
Title
A visual neural classifier
Author
Ornes, Chester ; Sklansky, Jack
Author_Institution
Dept. of Electr. & Comput. Eng., California Univ., Irvine, CA, USA
Volume
28
Issue
4
fYear
1998
fDate
8/1/1998 12:00:00 AM
Firstpage
620
Lastpage
625
Abstract
A new neural classifier allows visualization of the training set and decision regions, providing benefits for both the designer and the user. We demonstrate the visualization capabilities of this visual neural classifier using synthetic data, and compare the visualization performance to Kohunen´s self-organizing map. We show in applications to image segmentation and medical diagnosis that visualization enables a designer to refine the classifier to achieve low error rates and enhances a user´s ability to make classifier-assisted decisions
Keywords
data visualisation; image segmentation; learning (artificial intelligence); self-organising feature maps; Kohunen´s self-organizing map; classifier-assisted decisions; decision regions; image segmentation; low error rates; medical diagnosis; synthetic data; training set; visual neural classifier; visualization; Data visualization; Displays; Image segmentation; Lifting equipment; Medical diagnosis; Neck; Neural networks; Neurons; Nonhomogeneous media; Training data;
fLanguage
English
Journal_Title
Systems, Man, and Cybernetics, Part B: Cybernetics, IEEE Transactions on
Publisher
ieee
ISSN
1083-4419
Type
jour
DOI
10.1109/3477.704302
Filename
704302
Link To Document