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BMCBI
2010
103views more  BMCBI 2010»
14 years 9 months ago
MTRAP: Pairwise sequence alignment algorithm by a new measure based on transition probability between two consecutive pairs of r
Background: Sequence alignment is one of the most important techniques to analyze biological systems. It is also true that the alignment is not complete and we have to develop it ...
Toshihide Hara, Keiko Sato, Masanori Ohya
CVPR
2009
IEEE
16 years 4 months ago
A Min-Max Framework of Cascaded Classifier with Multiple Instance Learning for Computer Aided Diagnosis
The computer aided diagnosis (CAD) problems of detecting potentially diseased structures from medical images are typically distinguished by the following challenging characterist...
Dijia Wu (Rensselaer Polytechnic Institute), Jinbo...
CIVR
2008
Springer
271views Image Analysis» more  CIVR 2008»
14 years 11 months ago
Multiple feature fusion by subspace learning
Since the emergence of extensive multimedia data, feature fusion has been more and more important for image and video retrieval, indexing and annotation. Existing feature fusion t...
Yun Fu, Liangliang Cao, Guodong Guo, Thomas S. Hua...
ECCV
2010
Springer
14 years 10 months ago
MIForests: Multiple-Instance Learning with Randomized Trees
Abstract. Multiple-instance learning (MIL) allows for training classifiers from ambiguously labeled data. In computer vision, this learning paradigm has been recently used in many ...
Christian Leistner, Amir Saffari, Horst Bischof
PKDD
2010
Springer
178views Data Mining» more  PKDD 2010»
14 years 7 months ago
Graph Regularized Transductive Classification on Heterogeneous Information Networks
A heterogeneous information network is a network composed of multiple types of objects and links. Recently, it has been recognized that strongly-typed heterogeneous information net...
Ming Ji, Yizhou Sun, Marina Danilevsky, Jiawei Han...