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ICPR
2002
IEEE
14 years 9 months ago
Relational Graph Labelling Using Learning Techniques and Markov Random Fields
This paper introduces an approach for handling complex labelling problems driven by local constraints. The purpose is illustrated by two applications: detection of the road networ...
Denis Rivière, Jean-Francois Mangin, Jean-M...
ICCV
2007
IEEE
14 years 10 months ago
Classification of Weakly-Labeled Data with Partial Equivalence Relations
In many vision problems, instead of having fully labeled training data, it is easier to obtain the input in small groups, where the data in each group is constrained to be from th...
Sanjiv Kumar, Henry A. Rowley
ICTAI
2008
IEEE
14 years 2 months ago
Veritas: Combining Expert Opinions without Labeled Data
We consider a variation of the problem of combining expert opinions for the situation in which there is no ground truth to use for training. Even though we don’t have labeled da...
Sharath R. Cholleti, Sally A. Goldman, Avrim Blum,...
CVPR
2003
IEEE
14 years 10 months ago
Bootstrapping SVM Active Learning by Incorporating Unlabelled Images for Image Retrieval
The performance of image retrieval with SVM active learning is known to be poor when started with few labelled images only. In this paper, the problem is solved by incorporating t...
Lei Wang, Kap Luk Chan, Zhihua Zhang
ECCV
2010
Springer
14 years 1 months ago
Stacked Hierarchical Labeling
In this work we propose a hierarchical approach for labeling semantic objects and regions in scenes. Our approach is reminiscent of early vision literature in that we use a decompo...