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IJCAT
2010
133views more  IJCAT 2010»
13 years 6 months ago
A 3D shape classifier with neural network supervision
: The task of 3D shape classification is to assign a set of unordered shapes into pre-tagged classes with class labels, and find the most suitable class for a newly given shape. In...
Zhenbao Liu, Jun Mitani, Yukio Fukui, Seiichi Nish...
AIPR
2003
IEEE
13 years 11 months ago
Sensor and Classifier Fusion for Outdoor Obstacle Detection: an Application of Data Fusion To Autonomous Off-Road Navigation
This paper describes an approach for using several levels of data fusion in the domain of autonomous off-road navigation. We are focusing on outdoor obstacle detection, and we pre...
Cristian Dima, Nicolas Vandapel, Martial Hebert
EVOW
2008
Springer
13 years 10 months ago
A Hybrid Random Subspace Classifier Fusion Approach for Protein Mass Spectra Classification
Classifier fusion strategies have shown great potential to enhance the performance of pattern recognition systems. There is an agreement among researchers in classifier combination...
Amin Assareh, Mohammad Hassan Moradi, L. Gwenn Vol...
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...
ICML
2006
IEEE
14 years 9 months ago
How boosting the margin can also boost classifier complexity
Boosting methods are known not to usually overfit training data even as the size of the generated classifiers becomes large. Schapire et al. attempted to explain this phenomenon i...
Lev Reyzin, Robert E. Schapire