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» Learning the Relative Importance of Features in Image Data
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CVPR
2008
IEEE
14 years 10 months ago
Transfer learning for image classification with sparse prototype representations
To learn a new visual category from few examples, prior knowledge from unlabeled data as well as previous related categories may be useful. We develop a new method for transfer le...
Ariadna Quattoni, Michael Collins, Trevor Darrell
JMM2
2006
111views more  JMM2 2006»
13 years 8 months ago
A Microscopic Telepathology System for Multiresolution Computer-Aided Diagnostics
The aim of the presented system is simplification and speedup of the daily pathological examination routine. The system combines telepathology with computer-aided diagnostics algor...
Grigory Begelman, Michael Pechuk, Ehud Rivlin, Edm...
CVPR
2008
IEEE
14 years 10 months ago
Fast image search for learned metrics
We introduce a method that enables scalable image search for learned metrics. Given pairwise similarity and dissimilarity constraints between some images, we learn a Mahalanobis d...
Prateek Jain, Brian Kulis, Kristen Grauman
ICDM
2009
IEEE
233views Data Mining» more  ICDM 2009»
14 years 3 months ago
Semi-Supervised Sequence Labeling with Self-Learned Features
—Typical information extraction (IE) systems can be seen as tasks assigning labels to words in a natural language sequence. The performance is restricted by the availability of l...
Yanjun Qi, Pavel Kuksa, Ronan Collobert, Kunihiko ...
SG
2007
Springer
14 years 2 months ago
Data-Embeddable Texture Synthesis
Abstract. Data hiding techniques onto images provide tools for protecting copyright or sending secret messages, and they are currently utilized as a simple input device of a cell p...
Hirofumi Otori, Shigeru Kuriyama