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» Pattern Recognition Using Functions of Multiple Instances
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126
Voted
KDD
2006
ACM
129views Data Mining» more  KDD 2006»
16 years 2 months ago
Suppressing model overfitting in mining concept-drifting data streams
Mining data streams of changing class distributions is important for real-time business decision support. The stream classifier must evolve to reflect the current class distributi...
Haixun Wang, Jian Yin, Jian Pei, Philip S. Yu, Jef...
120
Voted
MM
2009
ACM
209views Multimedia» more  MM 2009»
15 years 9 months ago
Brain state decoding for rapid image retrieval
Human visual perception is able to recognize a wide range of targets under challenging conditions, but has limited throughput. Machine vision and automatic content analytics can p...
Jun Wang, Eric Pohlmeyer, Barbara Hanna, Yu-Gang J...
CVPR
1999
IEEE
16 years 4 months ago
Fundamental Bounds on Edge Detection: An Information Theoretic Evaluation of Different Edge Cues
We treat the problem of edge detection as one of statistical inference. Local edge cues, implemented by filters, provide information about the likely positions of edges which can ...
Scott Konishi, Alan L. Yuille, James M. Coughlan, ...
CVPR
2012
IEEE
13 years 4 months ago
Fixed-rank representation for unsupervised visual learning
Subspace clustering and feature extraction are two of the most commonly used unsupervised learning techniques in computer vision and pattern recognition. State-of-theart technique...
Risheng Liu, Zhouchen Lin, Fernando De la Torre, Z...
BMCBI
2006
116views more  BMCBI 2006»
15 years 2 months ago
ROKU: a novel method for identification of tissue-specific genes
Background: One of the important goals of microarray research is the identification of genes whose expression is considerably higher or lower in some tissues than in others. We wo...
Koji Kadota, Jiazhen Ye, Yuji Nakai, Tohru Terada,...