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» Learning Features by Contrasting Natural Images with Noise
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CVPR
2004
IEEE
14 years 9 months ago
Multiscale Conditional Random Fields for Image Labeling
We propose an approach to include contextual features for labeling images, in which each pixel is assigned to one of a finite set of labels. The features are incorporated into a p...
Miguel Á. Carreira-Perpiñán, ...
CGF
2008
89views more  CGF 2008»
13 years 8 months ago
Enhancement of Bright Video Features for HDR Displays
To utilize the full potential of new high dynamic range (HDR) displays, a system for the enhancement of bright luminous objects in video sequences is proposed. The system classifi...
Piotr Didyk, Rafal Mantiuk, Matthias Hein, Hans-Pe...
ICASSP
2011
IEEE
12 years 11 months ago
Deep belief nets for natural language call-routing
This paper considers application of Deep Belief Nets (DBNs) to natural language call routing. DBNs have been successfully applied to a number of tasks, including image, audio and ...
Ruhi Sarikaya, Geoffrey E. Hinton, Bhuvana Ramabha...
GRAPHITE
2005
ACM
14 years 1 months ago
Drawing the real
In this paper we present an algorithm to automatically produce artistic drawings from stereo image pairs. The input to the algorithm is a natural scene, along with a user-defined...
Danijela Markovic, Margrit Gelautz
ICIP
2007
IEEE
14 years 9 months ago
MuFeSaC: Learning When to Use Which Feature Detector
Interest point detectors are the starting point in image analysis for depth estimation using epipolar geometry and camera ego-motion estimation. With several detectors defined in ...
Sreenivas R. Sukumar, David L. Page, Hamparsum Boz...