Multiscale conditional random fields for machine vision
We develop a single joint model which can classify images and label super-pixels, based on tree-structured conditional random fields (CRFs) derived from a hierarchical image segmentation, extending previous work by Reynolds and Murphy, and Plath and Toussaint. We show how to train this model in a w...
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Language: | English |
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University of British Columbia
2010
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Online Access: | http://hdl.handle.net/2429/27032 |