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» Data Mining from Functional Brain Images
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116
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ICIP
2000
IEEE
16 years 6 months ago
Efficiently Estimating Projective Transformations
Projective transformations relate the coordinates of images that are taken by either a camera that undergoes only rotation while imaging an arbitrary scene, or one that rotates an...
Richard J. Radke, Peter J. Ramadge, Tomio Echigo, ...
144
Voted
KDD
2004
ACM
166views Data Mining» more  KDD 2004»
16 years 5 months ago
Predicting prostate cancer recurrence via maximizing the concordance index
In order to effectively use machine learning algorithms, e.g., neural networks, for the analysis of survival data, the correct treatment of censored data is crucial. The concordan...
Lian Yan, David Verbel, Olivier Saidi
132
Voted
BC
1998
111views more  BC 1998»
15 years 4 months ago
How to "hear" visual disparities: real-time stereoscopic spatial depth analysis using temporal resonance
Abstract. In a stereoscopic system, both eyes or cameras have a slightly di€erent view. As a consequence, small variations between the projected images exist (`disparities') ...
Bernd Porr, Alex Cozzi, Florentin Wörgöt...
PKDD
2010
Springer
164views Data Mining» more  PKDD 2010»
15 years 2 months ago
Complexity Bounds for Batch Active Learning in Classification
Active learning [1] is a branch of Machine Learning in which the learning algorithm, instead of being directly provided with pairs of problem instances and their solutions (their l...
Philippe Rolet, Olivier Teytaud
231
Voted
ICIP
2010
IEEE
15 years 2 months ago
Building Emerging Pattern (EP) Random forest for recognition
The Random forest classifier comes to be the working horse for visual recognition community. It predicts the class label of an input data by aggregating the votes of multiple tree...
Liang Wang, Yizhou Wang, Debin Zhao