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» Evaluating learning algorithms and classifiers
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CVPR
2007
IEEE
16 years 6 months ago
Detecting Pedestrians by Learning Shapelet Features
In this paper, we address the problem of detecting pedestrians in still images. We introduce an algorithm for learning shapelet features, a set of mid?level features. These featur...
Payam Sabzmeydani, Greg Mori
IAT
2010
IEEE
15 years 2 months ago
Design and Evaluation of Explainable BDI Agents
It is widely acknowledged that providing explanations is an important capability of intelligent systems. Explanation capabilities are useful, for example, in scenario-based traini...
Maaike Harbers, Karel van den Bosch, John-Jules Ch...
CVPR
2000
IEEE
16 years 6 months ago
Discriminant-EM Algorithm with Application to Image Retrieval
In Proc. of IEEE Conf. on CVPR'2000, Vol.I, pp.222-227, Hilton Head Island, SC, 2000 In many vision applications, the practice of supervised learning faces several difficulti...
Ying Wu, Qi Tian, Thomas S. Huang
AAAI
1998
15 years 5 months ago
Boosting in the Limit: Maximizing the Margin of Learned Ensembles
The "minimum margin" of an ensemble classifier on a given training set is, roughly speaking, the smallest vote it gives to any correct training label. Recent work has sh...
Adam J. Grove, Dale Schuurmans
ICPR
2004
IEEE
16 years 5 months ago
Fast Object and Pose Recognition Through Minimum Entropy Coding
We present a pattern recognizer to classify a variety of objects and their pose on a table from real world images. Learning of weights in a linear discriminant is based on estimat...
Günter Westphal, Rolf P. Würtz