DocumentCode
1131875
Title
Gray-scale ALIAS
Author
Bock, Peter ; Klinnert, Roland ; Kober, Rudolf ; Rovner, Richard M. ; Schmidt, Hauke
Author_Institution
Dept. of Electr. Eng. & Comput. Sci., George Washington Univ., DC, USA
Volume
4
Issue
2
fYear
1992
fDate
4/1/1992 12:00:00 AM
Firstpage
109
Lastpage
122
Abstract
Based on the paradigm of collective learning systems, ALIAS (adaptive learning image analysis system) is an adaptive image-processing engine specifically designed to detect anomalies in otherwise normal images and signals. To accomplish this, ALIAS requires only one pass through a training set, which typically consists of less than 100 samples. The original version of ALIAS (1.0) was limited to an input domain of binary images. A gray-scale version of ALIAS (2.3) was completed in Apr. 1991. The authors present the theoretical background and technical design of ALIAS and describe two experiments with the gray-scale capability
Keywords
computerised picture processing; learning systems; adaptive image-processing engine; binary images; collective learning systems; gray-scale version; training set; Adaptive signal detection; Adaptive systems; Computer architecture; Engines; Gray-scale; Humans; Image color analysis; Image processing; Machine learning; Signal design;
fLanguage
English
Journal_Title
Knowledge and Data Engineering, IEEE Transactions on
Publisher
ieee
ISSN
1041-4347
Type
jour
DOI
10.1109/69.134248
Filename
134248
Link To Document