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» On Combining Classifiers
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PAKDD
2011
ACM
245views Data Mining» more  PAKDD 2011»
12 years 11 months ago
Finding Rare Classes: Adapting Generative and Discriminative Models in Active Learning
Discovering rare categories and classifying new instances of them is an important data mining issue in many fields, but fully supervised learning of a rare class classifier is pr...
Timothy M. Hospedales, Shaogang Gong, Tao Xiang
BMCBI
2007
104views more  BMCBI 2007»
13 years 9 months ago
Using contextual and lexical features to restructure and validate the classification of biomedical concepts
Background: Biomedical ontologies are critical for integration of data from diverse sources and for use by knowledge-based biomedical applications, especially natural language pro...
Jung-Wei Fan, Hua Xu, Carol Friedman
TCSV
2008
313views more  TCSV 2008»
13 years 8 months ago
Fast Pedestrian Detection Using a Cascade of Boosted Covariance Features
Efficiently and accurately detecting pedestrians plays a very important role in many computer vision applications such as video surveillance and smart cars. In order to find the ri...
Sakrapee Paisitkriangkrai, Chunhua Shen, Jian Zhan...
AIEDU
2010
13 years 6 months ago
Supporting Collaborative Learning and E-Discussions Using Artificial Intelligence Techniques
An emerging trend in classrooms is the use of networked visual argumentation tools that allow students to discuss, debate, and argue with one another in a synchronous fashion about...
Bruce M. McLaren, Oliver Scheuer, Jan Miksatko
MIR
2010
ACM
325views Multimedia» more  MIR 2010»
13 years 10 months ago
A classification-driven similarity matching framework for retrieval of biomedical images
This paper presents a classification-driven biomedical image retrieval system to bride the semantic gap by transforming image features to their global categories at different gran...
Md. Mahmudur Rahman, Sameer Antani, George R. Thom...