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» Learning a Classification Model for Segmentation
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SIGIR
2008
ACM
15 years 2 months ago
Learning from labeled features using generalized expectation criteria
It is difficult to apply machine learning to new domains because often we lack labeled problem instances. In this paper, we provide a solution to this problem that leverages domai...
Gregory Druck, Gideon S. Mann, Andrew McCallum
153
Voted
SIGIR
2010
ACM
14 years 9 months ago
Temporally-aware algorithms for document classification
Automatic Document Classification (ADC) is still one of the major information retrieval problems. It usually employs a supervised learning strategy, where we first build a classif...
Thiago Salles, Leonardo C. da Rocha, Gisele L. Pap...
CCIA
2005
Springer
15 years 8 months ago
Classifying Natural Objects on Outdoor Scenes
We propose an hybrid and probabilistic classification of image regions belonging to scenes primarily containing natural objects, e.g. sky, trees, etc. as a first step in solving ...
Anna Bosch, Xavier Muñoz, Joan Martí...
168
Voted
BMCBI
2006
150views more  BMCBI 2006»
15 years 2 months ago
Instance-based concept learning from multiclass DNA microarray data
Background: Various statistical and machine learning methods have been successfully applied to the classification of DNA microarray data. Simple instance-based classifiers such as...
Daniel P. Berrar, Ian Bradbury, Werner Dubitzky
182
Voted
CVPR
2005
IEEE
16 years 4 months ago
Segmentation of Edge Preserving Gradient Vector Flow: An Approach Toward Automatically Initializing and Splitting of Snakes
Active contours or snakes have been extensively utilized in handling image segmentation and classification problems. In traditional active contour models, snake initialization is ...
Chunming Li, Jundong Liu, Martin D. Fox