We present a new unsupervised method to learn unified probabilistic object models (POMs) which can be applied to classification, segmentation, and recognition. We formulate this a...
Yuanhao Chen, Long Zhu, Alan L. Yuille, HongJiang ...
This is the sample implementation of a Markov random field based color image segmentation algorithm described in the following paper:
Zoltan Kato, Ting Chuen Pong, and John Chu...
This paper describes a hybrid model that combines machine learning with linguistic heuristics for integrating unknown word identification with Chinese word segmentation. The model...
This paper presents a Chinese word segmentation system which can adapt to different domains and standards. We first present a statistical framework where domain-specific words are...
This paper studies the problem of combining region and boundary cues for natural image segmentation. We employ a large database of manually segmented images in order to learn an o...