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» Unsupervised Feature Selection Using Feature Similarity
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BMCBI
2005
190views more  BMCBI 2005»
15 years 16 days ago
An Entropy-based gene selection method for cancer classification using microarray data
Background: Accurate diagnosis of cancer subtypes remains a challenging problem. Building classifiers based on gene expression data is a promising approach; yet the selection of n...
Xiaoxing Liu, Arun Krishnan, Adrian Mondry
130
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ICPR
2004
IEEE
16 years 1 months ago
Complex Human Activity Recognition for Monitoring Wide Outdoor Environments
The problem of automatic recognition of human activities is among the most important and challenging open areas of research in Computer Vision. This paper presents a new approach ...
Arcangelo Distante, I. Gnoni, Marco Leo, Paolo Spa...
122
Voted
BMCBI
2007
153views more  BMCBI 2007»
15 years 19 days ago
Analysis of nanopore detector measurements using Machine-Learning methods, with application to single-molecule kinetic analysis
Background: A nanopore detector has a nanometer-scale trans-membrane channel across which a potential difference is established, resulting in an ionic current through the channel ...
Matthew Landry, Stephen Winters-Hilt
IJCNN
2008
IEEE
15 years 7 months ago
Learning associations of conjuncted fuzzy sets for data prediction
— Fuzzy Associative Conjuncted Maps (FASCOM) is a fuzzy neural network that represents information by conjuncting fuzzy sets and associates them through a combination of unsuperv...
Hanlin Goh, Joo-Hwee Lim, Chai Quek
115
Voted
ICPR
2008
IEEE
15 years 7 months ago
Dual clustering for categorization of action sequences
This paper proposes a novel algorithm for categorization of action video sequences using unsupervised dual clustering. Given a video database, we extract motion information of act...
Joanna Cheng, Liang Wang, Christopher Leckie