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» Learning Visual Invariance
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CVPR
2012
IEEE
11 years 10 months ago
Robust Boltzmann Machines for recognition and denoising
While Boltzmann Machines have been successful at unsupervised learning and density modeling of images and speech data, they can be very sensitive to noise in the data. In this pap...
Yichuan Tang, Ruslan Salakhutdinov, Geoffrey E. Hi...
CVPR
2001
IEEE
14 years 9 months ago
Rapid Object Detection using a Boosted Cascade of Simple Features
This paper describes a machine learning approach for visual object detection which is capable of processing images extremely rapidly and achieving high detection rates. This wor...
Paul A. Viola, Michael J. Jones
ICPR
2008
IEEE
14 years 9 months ago
Evolving boundary detectors for natural images via Genetic Programming
Boundary detection constitutes a crucial step in many computer vision tasks. We present a novel learning approach to automatically construct a boundary detector for natural images...
Ilan Kadar, Moshe Sipper, Ohad Ben-Shahar
ISMAR
2009
IEEE
14 years 2 months ago
Advanced training methods using an Augmented Reality ultrasound simulator
Ultrasound (US) is a medical imaging modality which is extremely difficult to learn as it is user-dependent, has low image quality and many artifacts that depend on the viewing d...
Tobias Blum, Sandro Michael Heining, Oliver Kutter...
ICRA
2002
IEEE
148views Robotics» more  ICRA 2002»
14 years 23 days ago
A Neural Approach to Adaptive Behavior and Multi-Sensor Action Selection in a Mobile Device
Sampling multisensory information and taking the appropriate motor action is critical for a biological organism’s survival, but a difficult task for robots. We present a Neurally...
Jeffrey L. Krichmar, James A. Snook