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» Learning for Sequence Extraction Tasks
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ICML
2009
IEEE
14 years 4 months ago
Sparse higher order conditional random fields for improved sequence labeling
In real sequence labeling tasks, statistics of many higher order features are not sufficient due to the training data sparseness, very few of them are useful. We describe Sparse H...
Xian Qian, Xiaoqian Jiang, Qi Zhang, Xuanjing Huan...
ISBI
2004
IEEE
14 years 10 months ago
Hierarchical Segmentation of Multiple Sclerosis Lesions in Multi-Sequence MRI
Automatic segmentation of multiple sclerosis lesions in magnetic resonance images remains a challenging task. In this study, we present a fully automatic method to extract lesions...
Guillaume Dugas-Phocion, Miguel Ángel Gonz&...
ICIP
2003
IEEE
14 years 11 months ago
Adaptive rule-based recognition of events in video sequences
Knowledge-based fuzzy inference and neural learning are used in this paper in order to model the event recognition task in semantic video analysis. The advantage of their use is t...
Vassilis Tzouvaras, Gabriel Tsechpenakis, Giorgos ...
ISMB
1993
13 years 11 months ago
Prediction of Primate Splice Junction Gene Sequences with a Cooperative Knowledge Acquisition System
Wepropose a cooperative conceptual modelling environment in which two agents interact : the machineand the humanexpert. Theformer is able to extract knowledge from data using a sy...
Engelbert Mephu Nguifo, Jean Sallantin
ACL
2006
13 years 11 months ago
Exact Decoding for Jointly Labeling and Chunking Sequences
There are two decoding algorithms essential to the area of natural language processing. One is the Viterbi algorithm for linear-chain models, such as HMMs or CRFs. The other is th...
Nobuyuki Shimizu, Andrew R. Haas