Non-parametric higher-order random fields for image segmentation

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

Volumn 8694 LNCS, Issue PART 6, 2014, Pages 269-284

  Márquez Neila, Pablo ^a   Kohli, Pushmeet ^b   Rother, Carsten ^c   Baumela, Luis ^a  

^a UNIVERSIDAD POLITÉCNICA DE MADRID   (Spain)

^b MICROSOFT RESEARCH   (United Kingdom)

^c DRESDEN UNIVERSITY OF TECHNOLOGY   (Germany)

Author keywords

biomedical image analysis; higher order models; image denoising; image segmentation; random fields; structured prediction

Indexed keywords

IMAGE DENOISING; INFERENCE ENGINES;

BIOMEDICAL IMAGE ANALYSIS; EXACT REPRESENTATIONS; HIGHER-ORDER MODELS; INFERENCE ALGORITHM; RANDOM FIELDS; STRUCTURED PREDICTION; TOPOLOGICAL INFORMATION; TRANSFORMATION SCHEME;

IMAGE SEGMENTATION;

EID: 84906347640     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/978-3-319-10599-4_18     Document Type: Conference Paper

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