Effective semantic pixel labelling with convolutional networks and Conditional Random Fields

IEEE Computer Society Conference on Computer Vision and Pattern Recognition Workshops

Volumn 2015-October, Issue , 2015, Pages 36-43

  Paisitkriangkrai, Sakrapee ^a   Sherrah, Jamie ^a,b   Janney, Pranam ^b   Van Den Hengel, Anton ^a  

^a UNIVERSITY OF ADELAIDE   (Australia)

^b DEFENCE SCIENCE AND TECHNOLOGY ORGANISATION   (Australia)

Author keywords

Accuracy; Feature extraction; Image edge detection; Labeling; Semantics; Training; Visualization

Indexed keywords

CLASSIFICATION (OF INFORMATION); COMPUTER VISION; CONVOLUTION; DEEP NEURAL NETWORKS; EDGE DETECTION; FEATURE EXTRACTION; FLOW VISUALIZATION; LABELING; NEURAL NETWORKS; PERSONNEL TRAINING; PIXELS; SEMANTIC WEB; SEMANTICS;

ACCURACY; CLASS PROBABILITIES; CLASSIFICATION ACCURACY; CONDITIONAL RANDOM FIELD; CONDITIONAL RANDOM FIELDS(CRFS); CONVOLUTIONAL NETWORKS; CONVOLUTIONAL NEURAL NETWORK; IMAGE EDGE DETECTION;

RANDOM PROCESSES;

EID: 84940417787     PISSN: 21607508     EISSN: 21607516     Source Type: Conference Proceeding    
DOI: 10.1109/CVPRW.2015.7301381     Document Type: Conference Paper

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