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» Learning Mid-Level Features For Recognition
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RECOMB
2001
Springer
14 years 7 months ago
Predicting the beta-helix fold from protein sequence data
A method is presented that uses b-strand interactions to predict the parallel right-handed b-helix super-secondary structural motif in protein sequences. A program called BetaWrap...
Phil Bradley, Lenore Cowen, Matthew Menke, Jonatha...
ICPR
2008
IEEE
14 years 2 months ago
Adaptive nonstationary regression analysis
The problem of finding the most appropriate subset of features or regressors is the generic challenge of Machine Learning problems like regression estimation or pattern recognitio...
Olga Krasotkina, Vadim Mottl
ICIP
2007
IEEE
14 years 1 months ago
Propagating Image-Level Part Statistics to Enhance Object Detection
The bag-of-words approach has become increasingly attractive in the fields of object category recognition and scene classification, witnessed by some successful applications [5, 7...
Sheng Gao, Joo-Hwee Lim, Qibin Sun
GECCO
2005
Springer
218views Optimization» more  GECCO 2005»
14 years 1 months ago
Particle swarm optimization for analysis of mass spectral serum profiles
Serum profiling using mass spectrometry is an emerging technology with a great potential to provide biomarkers for complex diseases such as cancer. However, protein profiles obtai...
Habtom W. Ressom, Rency S. Varghese, Daniel Saha, ...
MM
2004
ACM
219views Multimedia» more  MM 2004»
14 years 29 days ago
Multi-level annotation of natural scenes using dominant image components and semantic concepts
Automatic image annotation is a promising solution to enable semantic image retrieval via keywords. In this paper, we propose a multi-level approach to annotate the semantics of n...
Jianping Fan, Yuli Gao, Hangzai Luo