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» Learning Object Context for Adaptive Learning Design
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SEDE
2007
13 years 10 months ago
BeLearning: Designing accessible web applications
Flexibility and adaptivity are two of the outstanding characteristics of new media and new technologies. These properties allow new methods to provide physically challenged people...
Helmut Vieritz, Sabina Jeschke
MM
2009
ACM
178views Multimedia» more  MM 2009»
14 years 3 months ago
Semantic context transfer across heterogeneous sources for domain adaptive video search
Automatic video search based on semantic concept detectors has recently received significant attention. Since the number of available detectors is much smaller than the size of h...
Yu-Gang Jiang, Chong-Wah Ngo, Shih-Fu Chang
CVPR
2009
IEEE
1002views Computer Vision» more  CVPR 2009»
15 years 3 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...
ML
2000
ACM
157views Machine Learning» more  ML 2000»
13 years 8 months ago
A Multistrategy Approach to Classifier Learning from Time Series
We present an approach to inductive concept learning using multiple models for time series. Our objective is to improve the efficiency and accuracy of concept learning by decomposi...
William H. Hsu, Sylvian R. Ray, David C. Wilkins
GECCO
2004
Springer
142views Optimization» more  GECCO 2004»
14 years 2 months ago
Improving MACS Thanks to a Comparison with 2TBNs
Abstract. Factored Markov Decision Processes is the theoretical framework underlying multi-step Learning Classifier Systems research. This framework is mostly used in the context ...
Olivier Sigaud, Thierry Gourdin, Pierre-Henri Wuil...