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» An Application of Boosting to Graph Classification
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ICCV
2009
IEEE
16 years 2 months ago
Is a detector only good for detection?
A common design of an object recognition system has two steps, a detection step followed by a foreground withinclass classification step. For example, consider face detection by...
Quan Yuan and Stan Sclaroff
CVPR
2006
IEEE
15 years 11 months ago
Supervised Learning of Edges and Object Boundaries
Edge detection is one of the most studied problems in computer vision, yet it remains a very challenging task. It is difficult since often the decision for an edge cannot be made ...
Piotr Dollár, Zhuowen Tu, Serge Belongie
ICCV
2007
IEEE
15 years 11 months ago
Locally Smooth Metric Learning with Application to Image Retrieval
In this paper, we propose a novel metric learning method based on regularized moving least squares. Unlike most previous metric learning methods which learn a global Mahalanobis d...
Dit-Yan Yeung, Hong Chang
IPPS
2002
IEEE
15 years 2 months ago
Concept-Based Component Libraries and Optimizing Compilers
This paper discusses concept lattices and some of their applications in component library development and compiler optimizations. Ongoing work on concept-based userextensible simp...
Sibylle Schupp, D. P. Gregor, B. Osman, David R. M...
EMNLP
2008
14 years 11 months ago
Soft-Supervised Learning for Text Classification
We propose a new graph-based semisupervised learning (SSL) algorithm and demonstrate its application to document categorization. Each document is represented by a vertex within a ...
Amarnag Subramanya, Jeff Bilmes