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CVPR
2006
IEEE
14 years 23 days ago
Learning Joint Top-Down and Bottom-up Processes for 3D Visual Inference
We present an algorithm for jointly learning a consistent bidirectional generative-recognition model that combines top-down and bottom-up processing for monocular 3d human motion ...
Cristian Sminchisescu, Atul Kanaujia, Dimitris N. ...
SC
2003
ACM
13 years 12 months ago
Identifying and Exploiting Spatial Regularity in Data Memory References
The growing processor/memory performance gap causes the performance of many codes to be limited by memory accesses. If known to exist in an application, strided memory accesses fo...
Tushar Mohan, Bronis R. de Supinski, Sally A. McKe...
IROS
2006
IEEE
180views Robotics» more  IROS 2006»
14 years 21 days ago
Real-Time Robot Audition System That Recognizes Simultaneous Speech in The Real World
— This paper presents a robot audition system that recognizes simultaneous speech in the real world by using robotembedded microphones. We have previously reported Missing Featur...
Shun'ichi Yamamoto, Kazuhiro Nakadai, Mikio Nakano...
CVPR
2009
IEEE
15 years 1 months ago
A Min-Max Framework of Cascaded Classifier with Multiple Instance Learning for Computer Aided Diagnosis
The computer aided diagnosis (CAD) problems of detecting potentially diseased structures from medical images are typically distinguished by the following challenging characterist...
Dijia Wu (Rensselaer Polytechnic Institute), Jinbo...
ECCV
2010
Springer
13 years 6 months ago
MIForests: Multiple-Instance Learning with Randomized Trees
Abstract. Multiple-instance learning (MIL) allows for training classifiers from ambiguously labeled data. In computer vision, this learning paradigm has been recently used in many ...
Christian Leistner, Amir Saffari, Horst Bischof