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ACL
2006
13 years 7 months ago
Semi-Supervised Conditional Random Fields for Improved Sequence Segmentation and Labeling
We present a new semi-supervised training procedure for conditional random fields (CRFs) that can be used to train sequence segmentors and labelers from a combination of labeled a...
Feng Jiao, Shaojun Wang, Chi-Hoon Lee, Russell Gre...
ICIP
2005
IEEE
14 years 7 months ago
An active regions approach for the segmentation of 3D biological tissue
Some of the most successful algorithms for the automated segmentation of images use an Active Regions approach, where a curve is evolved so as to maximize the disparity of its int...
Gregory Randall, Juan Cardelino, Marcelo Bertalm&i...
ICDM
2006
IEEE
135views Data Mining» more  ICDM 2006»
14 years 1 days ago
Discovering Frequent Poly-Regions in DNA Sequences
The problem of discovering arrangements of regions of high occurrence of one or more items of a given alphabet in a sequence, is studied, and two efficient approaches are propose...
Panagiotis Papapetrou, Gary Benson, George Kollios
RECOMB
2005
Springer
14 years 6 months ago
Learning Interpretable SVMs for Biological Sequence Classification
Background: Support Vector Machines (SVMs) ? using a variety of string kernels ? have been successfully applied to biological sequence classification problems. While SVMs achieve ...
Christin Schäfer, Gunnar Rätsch, Sö...
BMCBI
2010
142views more  BMCBI 2010»
13 years 6 months ago
Classification of protein sequences by means of irredundant patterns
Background: The classification of protein sequences using string algorithms provides valuable insights for protein function prediction. Several methods, based on a variety of diff...
Matteo Comin, Davide Verzotto