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» Learning to Classify X-Ray Images Using Relational Learning
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111
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CIARP
2008
Springer
15 years 4 months ago
Learning and Forgetting with Local Information of New Objects
The performance of supervised learners depends on the presence of a relatively large labeled sample. This paper proposes an automatic ongoing learning system, which is able to inco...
Fernando Vázquez, José Salvador S&aa...
128
Voted
BIBE
2007
IEEE
124views Bioinformatics» more  BIBE 2007»
15 years 8 months ago
Finding Cancer-Related Gene Combinations Using a Molecular Evolutionary Algorithm
—High-throughput data such as microarrays make it possible to investigate the molecular-level mechanism of cancer more efficiently. Computational methods boost the microarray ana...
Chan-Hoon Park, Soo-Jin Kim, Sun Kim, Dong-Yeon Ch...
142
Voted
CISST
2004
164views Hardware» more  CISST 2004»
15 years 4 months ago
Probabilistic Region Relevance Learning for Content-Based Image Retrieval
Probabilistic feature relevance learning (PFRL) is an effective method for adaptively computing local feature relevance in content-based image retrieval. It computes flexible retr...
Iker Gondra, Douglas R. Heisterkamp
112
Voted
ICPR
2008
IEEE
16 years 3 months ago
Texture classification with minimal training images
The objective of this work is classifying texture from a single image under unknown lighting conditions. The current and successful approach to this task is to treat it as a stati...
Alireza Tavakoli Targhi, Jan-Mark Geusebroek, Andr...
126
Voted
CVPR
2009
IEEE
1002views Computer Vision» more  CVPR 2009»
16 years 9 months ago
Classifier Grids for Robust Adaptive Object Detection
In this paper we present an adaptive but robust object detector for static cameras by introducing classifier grids. Instead of using a sliding window for object detection we pro...
Peter M. Roth, Sabine Sternig, Helmut Grabner, Hor...