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» Learning the Relative Importance of Features in Image Data
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TKDE
2010
224views more  TKDE 2010»
13 years 3 months ago
Non-Negative Matrix Factorization for Semisupervised Heterogeneous Data Coclustering
Coclustering heterogeneous data has attracted extensive attention recently due to its high impact on various important applications, such us text mining, image retrieval, and bioin...
Yanhua Chen, Lijun Wang, Ming Dong
BMCBI
2007
133views more  BMCBI 2007»
13 years 8 months ago
Semi-supervised learning for the identification of syn-expressed genes from fused microarray and in situ image data
Background: Gene expression measurements during the development of the fly Drosophila melanogaster are routinely used to find functional modules of temporally co-expressed genes. ...
Ivan G. Costa, Roland Krause, Lennart Opitz, Alexa...
ISCIS
2003
Springer
14 years 1 months ago
Comparison of Feature Sets Using Multimedia Translation
Feature selection is very important for many computer vision applications. However, it is hard to find a good measure for the comparison. In this study, feature sets are compared ...
Pinar Duygulu, Özge Can Özcanli, Norman ...
DAGM
2007
Springer
14 years 2 months ago
Classifying Glaucoma with Image-Based Features from Fundus Photographs
Glaucoma is one of the most common causes of blindness and it is becoming even more important considering the ageing society. Because healing of died retinal nerve fibers is not p...
Rüdiger Bock, Jörg Meier, Georg Michelso...
KDD
1995
ACM
148views Data Mining» more  KDD 1995»
14 years 5 days ago
Learning Arbiter and Combiner Trees from Partitioned Data for Scaling Machine Learning
Knowledge discovery in databases has become an increasingly important research topic with the advent of wide area network computing. One of the crucial problems we study in this p...
Philip K. Chan, Salvatore J. Stolfo