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» Unsupervised feature selection using a neuro-fuzzy approach
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ICML
2009
IEEE
16 years 19 days ago
Multi-class image segmentation using conditional random fields and global classification
A key aspect of semantic image segmentation is to integrate local and global features for the prediction of local segment labels. We present an approach to multi-class segmentatio...
Nils Plath, Marc Toussaint, Shinichi Nakajima
ICONIP
2008
15 years 1 months ago
Local Feature Selection in Text Clustering
Abstract. Feature selection has improved the performance of text clustering. Global feature selection tries to identify a single subset of features which are relevant to all cluste...
Marcelo N. Ribeiro, Manoel J. R. Neto, Ricardo Bas...
ICDAR
2009
IEEE
15 years 6 months ago
Generic Feature Selection and Document Processing
This paper presents a generic features selection method and its applications on some document analysis problems. The method is based on a genetic algorithm (GA), whose tness funct...
Hassan Chouaib, Nicole Vincent, Florence Cloppet, ...
ICASSP
2011
IEEE
14 years 3 months ago
Detection of anomalous events from unlabeled sensor data in smart building environments
This paper presents a robust unsupervised learning approach for detection of anomalies in patterns of human behavior using multi-modal smart environment sensor data. We model the ...
Padmini Jaikumar, Aca Gacic, Burton Andrews, Micha...
ICCV
2011
IEEE
13 years 12 months ago
A Linear Subspace Learning Approach via Sparse Coding
Linear subspace learning (LSL) is a popular approach to image recognition and it aims to reveal the essential features of high dimensional data, e.g., facial images, in a lower di...
Lei Zhang, Pengfei Zhu, Qinghu Hu, David Zhang