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» Unsupervised Learning for Graph Matching
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COLING
2010
14 years 9 months ago
Improved Discriminative ITG Alignment using Hierarchical Phrase Pairs and Semi-supervised Training
While ITG has many desirable properties for word alignment, it still suffers from the limitation of one-to-one matching. While existing approaches relax this limitation using phra...
Shujie Liu, Chi-Ho Li, Ming Zhou
186
Voted
ICASSP
2011
IEEE
14 years 5 months ago
A fully automated 2-DE gel image analysis pipeline for high throughput proteomics
Image analysis is still considered as the bottleneck in 2D-gel based expression proteomics analysis for biomarkers discovery. We are presenting a new end-to-end image analysis pip...
Panagiotis Tsakanikas, Elias S. Manolakos
VIP
2003
15 years 3 months ago
Using Dual Cascading Learning Frameworks for Image Indexing
To bridge the semantic gap in content-based image retrieval, detecting meaningful visual entities (e.g. faces, sky, foliage, buildings etc) in image content and classifying images...
Joo-Hwee Lim, Jesse S. Jin
123
Voted
CVIU
2008
188views more  CVIU 2008»
15 years 2 months ago
Learning function-based object classification from 3D imagery
We propose a novel scheme for using supervised learning for function-based classification of objects in 3D images. During the learning process, a generic multi-level hierarchical ...
Michael Pechuk, Octavian Soldea, Ehud Rivlin
121
Voted
AAAI
2012
13 years 4 months ago
Dynamic Matching via Weighted Myopia with Application to Kidney Exchange
In many dynamic matching applications—especially high-stakes ones—the competitive ratios of prior-free online algorithms are unacceptably poor. The algorithm should take distr...
John P. Dickerson, Ariel D. Procaccia, Tuomas Sand...