Classification of surface defects on hot rolled steel using adaptive learning methods

4th International Conference on Knowledge-Based Intelligent Engineering Systems and Allied Technologies, KES 2000 - Proceedings

Volumn 1, Issue , 2000, Pages 103-108

  Caleb, P ^a   Steuer, M ^a  

^a UNIVERSITY OF THE WEST OF ENGLAND   (United Kingdom)

Author keywords

[No Author keywords available]

Indexed keywords

ARTIFICIAL INTELLIGENCE; DECISION SUPPORT SYSTEMS; LEARNING SYSTEMS; COMPUTATIONAL COMPLEXITY; DEFECTS; HOT ROLLING; IMAGE SENSORS; STEEL;

ADAPTIVE COMPUTING; ADAPTIVE LEARNING METHOD; COMPUTING TECHNIQUES; HOT ROLLED STEELS; LOCAL AREAS; SUPERVISED AND UNSUPERVISED LEARNING;

SURFACE DEFECTS; SURFACE TESTING;

ADAPTIVE LEARNING METHODS;

EID: 0033659709     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/KES.2000.885769     Document Type: Conference Paper

References (4)

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4. Ultsch A. "Self-organising Neural Networks for Visualisation and Classification". Department of Computer Science, University of Dortmund, P.O.Box 500, D-4600 Dortmund 50, Germany. Report.