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TKDE
2010
168views more  TKDE 2010»
13 years 6 months ago
Completely Lazy Learning
—Local classifiers are sometimes called lazy learners because they do not train a classifier until presented with a test sample. However, such methods are generally not complet...
Eric K. Garcia, Sergey Feldman, Maya R. Gupta, San...
MICCAI
2005
Springer
14 years 1 months ago
Automatic 4-D Registration in Dynamic MR Renography Based on Over-Complete Dyadic Wavelet and Fourier Transforms
Dynamic contrast-enhanced 4-D MR renography has the potential for broad clinical applications, but suffers from respiratory motion that limits analysis and interpretation. Since ea...
Ting Song, Vivian S. Lee, Henry Rusinek, Manmeen K...
ECCV
2010
Springer
14 years 1 days ago
Efficient Highly Over-Complete Sparse Coding using a Mixture Model
Sparse coding of sensory data has recently attracted notable attention in research of learning useful features from the unlabeled data. Empirical studies show that mapping the data...
PATAT
2000
Springer
89views Education» more  PATAT 2000»
13 years 11 months ago
A Language for Specifying Complete Timetabling Problems
The timetabling problem consists in fixing a sequence of meetings between teachers and students in a given period of time, satisfying a set of different constraints. There are a nu...
Luís Paulo Reis, Eugenio Oliveira
CORR
2010
Springer
238views Education» more  CORR 2010»
13 years 7 months ago
Face Identification by SIFT-based Complete Graph Topology
This paper presents a new face identification system based on Graph Matching Technique on SIFT features extracted from face images. Although SIFT features have been successfully us...
Dakshina Ranjan Kisku, Ajita Rattani, Enrico Gross...