A fast learning algorithm for image segmentation with max-pooling convolutional networks

2013 IEEE International Conference on Image Processing, ICIP 2013 - Proceedings

Volumn , Issue , 2013, Pages 2713-2717

  Masci, Jonathan ^a   Giusti, Alessandro ^a   Ciresan, Dan ^a   Fricout, Gabriel ^b   Schmidhuber, Jurgen ^a  

^a DALLE MOLLE INSTITUTE FOR ARTIFICIAL INTELLIGENCE IDSIA   (Switzerland)

^b ARCELORMITTAL   (France)

Author keywords

Convolutional Network; Detection; Industrial Application; Medical Imaging; Segmentation

Indexed keywords

CONVOLUTION; ERROR DETECTION; IMAGE SEGMENTATION; INDUSTRIAL APPLICATIONS; LEARNING ALGORITHMS; MEDICAL IMAGING;

CONVOLUTIONAL NETWORKS; FAST ALGORITHMS; MAX-POOLING; RECORD-BREAKING PERFORMANCE; SINGLE PASS; SPEED UP; STEEL DEFECT; TRAINING IMAGE;

CONVOLUTIONAL NEURAL NETWORKS;

EID: 84897756043     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/ICIP.2013.6738559     Document Type: Conference Paper

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