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CVPR
2012
IEEE
12 years 14 days 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...
DAGM
2005
Springer
14 years 3 months ago
Object Categorization and the Need for Many-to-Many Matching
Abstract. Object recognition systems have their roots in the AI community, and originally addressed the problem of object categorization. These early systems, however, were limited...
Sven J. Dickinson, Ali Shokoufandeh, Yakov Keselma...
CVPR
2003
IEEE
15 years 1 days ago
Object Class Recognition by Unsupervised Scale-Invariant Learning
We present a method to learn and recognize object class models from unlabeled and unsegmented cluttered scenes in a scale invariant manner. Objects are modeled as flexible constel...
Robert Fergus, Pietro Perona, Andrew Zisserman
ICRA
2007
IEEE
125views Robotics» more  ICRA 2007»
14 years 4 months ago
EigenNail for Finger Force Direction Recognition
Abstract— This paper presents a technique termed EigenNails to classify fingertip force during contact based on the coloration patterns in the fingernail and surrounding skin. ...
Yu Sun, John M. Hollerbach, Stephen A. Mascaro
ACCV
2007
Springer
14 years 4 months ago
The Kernel Orthogonal Mutual Subspace Method and Its Application to 3D Object Recognition
This paper proposes the kernel orthogonal mutual subspace method (KOMSM) for 3D object recognition. KOMSM is a kernel-based method for classifying sets of patterns such as video fr...
Kazuhiro Fukui, Osamu Yamaguchi