One-class classification for Anomaly Detection in Wire Ropes with Gaussian processes in a few lines of code

Proceedings of the 12th IAPR Conference on Machine Vision Applications, MVA 2011

Volumn , Issue , 2011, Pages 219-222

  Rodner, Erik ^a   Wacker, Esther Sabrina ^a   Kemmler, Michael ^a   Denzler, Joachim ^a  

^a FRIEDRICH SCHILLER UNIVERSITY JENA   (Germany)

Author keywords

[No Author keywords available]

Indexed keywords

ANOMALY DETECTION; BAYESIAN FRAMEWORKS; DEFECT LOCALIZATIONS; GAUSSIAN PROCESS; GAUSSIAN PROCESSES; KERNEL FUNCTION; LINES OF CODE; NON-PARAMETRIC; ONE-CLASS CLASSIFICATION; STATE OF THE ART; SUPPORT VECTOR DATA DESCRIPTION; VISUAL APPEARANCE;

COMPUTER VISION; DATA DESCRIPTION; GAUSSIAN DISTRIBUTION; GAUSSIAN NOISE (ELECTRONIC); SURFACE DEFECTS;

WIRE ROPE;

EID: 84872513695     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper

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