338 search results - page 18 / 68 » Learning Flexible Features for Conditional Random Fields |
CVBIA
2005
Springer
15 years 3 months ago
2005
Springer
Abstract. Markov Random Fields (MRFs) are a popular and wellmotivated model for many medical image processing tasks such as segmentation. Discriminative Random Fields (DRFs), a dis...
60
Voted
IJCNLP
2005
Springer
15 years 3 months ago
2005
Springer
Recent work on Conditional Random Fields (CRFs) has demonstrated the need for regularisation when applying these models to real-world NLP data sets. Conventional approaches to regu...
128
Voted
ICDAR
2009
IEEE
14 years 7 months ago
2009
IEEE
The paper describes a new approach using a Conditional Random Fields (CRFs) to extract physical and logical layouts in unconstrained handwritten letters such as those sent by indi...
CVPR
2010
IEEE
15 years 5 months ago
2010
IEEE
Detecting and segmenting cell regions in microscopic images is a challenging task, because cells typically do not have rich features, and their shapes and appearances are highly i...
108
click to vote
KDD
2010
ACM
15 years 1 months ago
2010
ACM
Feature selection is an important task in order to achieve better generalizability in high dimensional learning, and structure learning of Markov random fields (MRFs) can automat...