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» Objective reduction using a feature selection technique
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ICDM
2006
IEEE
131views Data Mining» more  ICDM 2006»
14 years 3 months ago
Dimension Reduction for Supervised Ordering
Ordered lists of objects are widely used as representational forms. Such ordered objects include Web search results and best-seller lists. Techniques for processing such ordinal d...
Toshihiro Kamishima, Shotaro Akaho
AVSS
2009
IEEE
14 years 2 months ago
Comparative Evaluation of Stationary Foreground Object Detection Algorithms Based on Background Subtraction Techniques
In several video surveillance applications, such as the detection of abandoned/stolen objects or parked vehicles, the detection of stationary foreground objects is a critical task...
Álvaro Bayona, Juan Carlos San Miguel, Jos&...
WACV
2005
IEEE
14 years 2 months ago
Using Co-Occurrence and Segmentation to Learn Feature-Based Object Models from Video
A number of recent systems for unsupervised featurebased learning of object models take advantage of cooccurrence: broadly, they search for clusters of discriminative features tha...
Thomas S. Stepleton, Tai Sing Lee
ICDM
2009
IEEE
156views Data Mining» more  ICDM 2009»
13 years 6 months ago
Scalable Classification in Large Scale Spatiotemporal Domains Applied to Voltage-Sensitive Dye Imaging
We present an approach for learning models that obtain accurate classification of large scale data objects, collected in spatiotemporal domains. The model generation is structured ...
Igor Vainer, Sarit Kraus, Gal A. Kaminka, Hamutal ...
DAC
2009
ACM
14 years 4 months ago
ARMS - automatic residue-minimization based sampling for multi-point modeling techniques
This paper describes an automatic methodology for optimizing sample point selection for using in the framework of model order reduction (MOR). The procedure, based on the maximiza...
Jorge Fernandez Villena, Luis Miguel Silveira