Markov random field models provide a robust formulation of low-level vision problems. Among the problems, stereo vision remains the most investigated field. The belief propagation...
Word clustering is a conventional and important NLP task, and the literature has suggested two kinds of approaches to this problem. One is based on the distributional similarity a...
In a sensor network there are many paths between a source and a destination. An efficient method to explore and navigate in the ‘path space’ can help many important routing p...
This paper presents a dynamic conditional random field (DCRF) model to integrate contextual constraints for object segmentation in image sequences. Spatial and temporal dependenci...
This paper describes an online handwritten Japanese character string recognition system based on conditional random fields, which integrates the information of character recogniti...