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» Learning on the Test Data: Leveraging Unseen Features
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JMLR
2010
155views more  JMLR 2010»
13 years 7 months ago
Approximate Tree Kernels
Convolution kernels for trees provide simple means for learning with tree-structured data. The computation time of tree kernels is quadratic in the size of the trees, since all pa...
Konrad Rieck, Tammo Krueger, Ulf Brefeld, Klaus-Ro...
3DPVT
2006
IEEE
247views Visualization» more  3DPVT 2006»
14 years 26 days ago
Contour-Based Object Detection in Range Images
This paper presents a novel object recognition approach based on range images. Due to its insensitivity to illumination, range data is well suited for reliable silhouette extracti...
Stefan Stiene, Kai Lingemann, Andreas Nüchter...
ICIAR
2009
Springer
13 years 6 months ago
A Robust Modular Wavelet Network Based Symbol Classifier
This paper presents a robust automatic shape classifier using modular wavelet networks (MWNs). A shape descriptor is constructed based on a combination of global geometric features...
Akshaya Kumar Mishra, Paul W. Fieguth, David A. Cl...
ECCV
2006
Springer
14 years 11 months ago
Weakly Supervised Learning of Part-Based Spatial Models for Visual Object Recognition
Abstract. In this paper we investigate a new method of learning partbased models for visual object recognition, from training data that only provides information about class member...
David J. Crandall, Daniel P. Huttenlocher
ICCV
2005
IEEE
14 years 2 months ago
Image Based Regression Using Boosting Method
We present a general algorithm of image based regression that is applicable to many vision problems. The proposed regressor that targets a multiple-output setting is learned using...
Shaohua Kevin Zhou, Bogdan Georgescu, Xiang Sean Z...