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» Learning Kernel Expansions for Image Classification
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NIPS
2008
13 years 9 months ago
Supervised Dictionary Learning
It is now well established that sparse signal models are well suited for restoration tasks and can be effectively learned from audio, image, and video data. Recent research has be...
Julien Mairal, Francis Bach, Jean Ponce, Guillermo...
CVPR
2009
IEEE
15 years 2 months ago
Echocardiogram View Classification using Edge Filtered Scale-invariant Motion Features
In an 2D echocardiogram exam, an ultrasound probe samples the heart with 2D slices. Changing the orientation and position on the probe changes the slice viewpoint, altering the ...
Ritwik Kumar, Fei Wang, David Beymer, Tanveer Fath...
MICCAI
2000
Springer
13 years 11 months ago
Small Sample Size Learning for Shape Analysis of Anatomical Structures
We present a novel approach to statistical shape analysis of anatomical structures based on small sample size learning techniques. The high complexity of shape models used in medic...
Polina Golland, W. Eric L. Grimson, Martha Elizabe...
KDD
2008
ACM
104views Data Mining» more  KDD 2008»
14 years 8 months ago
Learning methods for lung tumor markerless gating in image-guided radiotherapy
In an idealized gated radiotherapy treatment, radiation is delivered only when the tumor is at the right position. For gated lung cancer radiotherapy, it is difficult to generate ...
Ying Cui, Jennifer G. Dy, Gregory C. Sharp, Brian ...
CVPR
2009
IEEE
1096views Computer Vision» more  CVPR 2009»
15 years 2 months ago
How far can you get with a modern face recognition test set using only simple features?
In recent years, large databases of natural images have become increasingly popular in the evaluation of face and object recognition algorithms. However, Pinto et al. previously ...
Nicolas Pinto, James J. DiCarlo, David D. Cox