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» Robust feature induction for support vector machines
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CVBIA
2005
Springer
15 years 3 months ago
Segmenting Brain Tumors with Conditional Random Fields and Support Vector Machines
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...
Chi-Hoon Lee, Mark Schmidt, Albert Murtha, Aalo Bi...
CVPR
2004
IEEE
15 years 1 months ago
Learning in Region-Based Image Retrieval with Generalized Support Vector Machines
Relevance feedback approaches based on support vector machine (SVM) learning have been applied to significantly improve retrieval performance in content-based image retrieval (CBI...
Iker Gondra, Douglas R. Heisterkamp
71
Voted
NIPS
2007
14 years 11 months ago
Discriminative Keyword Selection Using Support Vector Machines
Many tasks in speech processing involve classification of long term characteristics of a speech segment such as language, speaker, dialect, or topic. A natural technique for dete...
William M. Campbell, Fred S. Richardson
EVOW
2006
Springer
15 years 1 months ago
Robust SVM-Based Biomarker Selection with Noisy Mass Spectrometric Proteomic Data
Abstract. Computational analysis of mass spectrometric (MS) proteomic data from sera is of potential relevance for diagnosis, prognosis, choice of therapy, and study of disease act...
Elena Marchiori, Connie R. Jimenez, Mikkel West-Ni...
BMCBI
2007
127views more  BMCBI 2007»
14 years 9 months ago
Predicting the phenotypic effects of non-synonymous single nucleotide polymorphisms based on support vector machines
Background: Human genetic variations primarily result from single nucleotide polymorphisms (SNPs) that occur approximately every 1000 bases in the overall human population. The no...
Jian Tian, Ningfeng Wu, Xuexia Guo, Jun Guo, Juhua...