Process knowledge based multi-class support vector classification (PK-MSVM) approach for surface defects in hot rolling

Expert Systems with Applications

Volumn 38, Issue 6, 2011, Pages 7251-7262

  Agarwal, Kuldeep ^a   Shivpuri, Rajiv ^a   Zhu, Yijun ^a   Chang, Tzyy Shuh ^b   Huang, Howard ^b  

^a The Ohio State University   (United States)

^b OG Technologies Inc   (United States)

Author keywords

Automated inspection; Classification; Hot bar rolling; Image processing; Process knowledge; Support vector machines

Indexed keywords

AUTOMATED INSPECTION; AUTOMATED TECHNIQUES; BAR ROLLING; CLASSIFICATION; HOT BAR ROLLING; IMAGE PROCESSING ALGORITHM; IMAGING SENSORS; LENGTH-TO-WIDTH RATIO; MANUAL INSPECTION; MULTI-CLASS; MULTI-CLASS SUPPORT VECTOR MACHINES; MULTICLASS SVM; NEW APPROACHES; OBSERVATION DATA; ON-MACHINES; PRIMARY SOURCES; PROCESS KNOWLEDGE; ROLLING PROCESS; STATISTICAL INFERENCE; SUPPORT VECTOR CLASSIFICATION; THERMO-MECHANICS;

ALGORITHMS; AUTOMATION; COMPUTER VISION; FEATURE EXTRACTION; HOT ROLLING; IMAGING SYSTEMS; INFERENCE ENGINES; INSPECTION; KNOWLEDGE BASED SYSTEMS; METAL WORKING; SUPPORT VECTOR MACHINES; VECTORS;

SURFACE DEFECTS;

EID: 79951578017     PISSN: 09574174     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.eswa.2010.12.026     Document Type: Article

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