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» Exploiting multiple classifier types with active learning
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ICDM
2009
IEEE
172views Data Mining» more  ICDM 2009»
13 years 5 months ago
Evaluating Statistical Tests for Within-Network Classifiers of Relational Data
Recently a number of modeling techniques have been developed for data mining and machine learning in relational and network domains where the instances are not independent and ide...
Jennifer Neville, Brian Gallagher, Tina Eliassi-Ra...
PR
2008
91views more  PR 2008»
13 years 7 months ago
Applying the multi-category learning to multiple video object extraction
Video object (VO) extraction is of great importance in multimedia processing. In recent years approaches have been proposed to deal with VO extraction as a classification problem....
Yi Liu, Yuan F. Zheng, Xiaotong Shen
CCIA
2005
Springer
14 years 28 days 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...
AAAI
1996
13 years 8 months ago
A Hybrid Learning Approach for Better Recognition of Visual Objects
Real world images often contain similar objects but with different rotations, noise, or other visual alterations. Vision systems should be able to recognize objects regardless of ...
Ibrahim F. Imam, Srinivas Gutta
ESANN
2006
13 years 8 months ago
Margin based Active Learning for LVQ Networks
In this article, we extend a local prototype-based learning model by active learning, which gives the learner the capability to select training samples during the model adaptation...
Frank-Michael Schleif, Barbara Hammer, Thomas Vill...