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» Learning Visual Invariance
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ICMLA
2010
13 years 5 months ago
Semi-Supervised Anomaly Detection for EEG Waveforms Using Deep Belief Nets
Abstract--Clinical electroencephalography (EEG) is routinely used to monitor brain function in critically ill patients, and specific EEG waveforms are recognized by clinicians as s...
Drausin Wulsin, Justin Blanco, Ram Mani, Brian Lit...
ICCV
2011
IEEE
12 years 7 months ago
Struck: Structured Output Tracking with Kernels
Adaptive tracking-by-detection methods are widely used in computer vision for tracking arbitrary objects. Current approaches treat the tracking problem as a classification task a...
Sam Hare, Amir Saffari, Philip H.S. Torr
CVPR
2005
IEEE
14 years 9 months ago
Cloth Representation by Shape from Shading with Shading Primitives
Cloth is a complex visual pattern with flexible 3D shape and illumination variations. Computing the 3D shape of cloth from a single image is of great interest to both computer gra...
Feng Han, Song Chun Zhu
CVPR
2007
IEEE
14 years 9 months ago
Region Classification with Markov Field Aspect Models
Considerable advances have been made in learning to recognize and localize visual object classes. Simple bag-offeature approaches label each pixel or patch independently. More adv...
Jakob J. Verbeek, Bill Triggs
CVPR
2008
IEEE
14 years 9 months ago
Small codes and large image databases for recognition
The Internet contains billions of images, freely available online. Methods for efficiently searching this incredibly rich resource are vital for a large number of applications. Th...
Antonio B. Torralba, Robert Fergus, Yair Weiss