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CVPR
2007
IEEE
14 years 16 days ago
Diverse Active Ranking for Multimedia Search
Interactively learning from a small sample of unlabeled examples is an enormously challenging task, one that often arises in vision applications. Relevance feedback and more recen...
ShyamSundar Rajaram, Charlie K. Dagli, Nemanja Pet...
DM
2006
86views more  DM 2006»
13 years 8 months ago
Minimal rankings and the arank number of a path
Given a graph G, a function f : V (G) {1, 2, . . . , k} is a k-ranking of G if f (u) = f (v) implies every u - v path contains a vertex w such that f (w) > f (u). A k-ranking ...
Victor Kostyuk, Darren A. Narayan, Victoria A. Wil...
PAMI
2012
11 years 11 months ago
CPMC: Automatic Object Segmentation Using Constrained Parametric Min-Cuts
—We present a novel framework to generate and rank plausible hypotheses for the spatial extent of objects in images using bottom-up computational processes and mid-level selectio...
João Carreira, Cristian Sminchisescu
COLING
2010
13 years 3 months ago
Cross-Market Model Adaptation with Pairwise Preference Data for Web Search Ranking
Machine-learned ranking techniques automatically learn a complex document ranking function given training data. These techniques have demonstrated the effectiveness and flexibilit...
Jing Bai, Fernando Diaz, Yi Chang, Zhaohui Zheng, ...
AMR
2007
Springer
160views Multimedia» more  AMR 2007»
14 years 2 months ago
Improving Automatic Image Annotation Based on Word Co-occurrence
Abstract. Accuracy of current automatic image labeling methods is under the requirements of annotation-based image retrieval systems. The performance of most of these labeling meth...
Hugo Jair Escalante, Manuel Montes-y-Gómez,...