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» Learning Features by Contrasting Natural Images with Noise
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CVPR
2004
IEEE
16 years 1 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»
14 years 11 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
14 years 3 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
15 years 5 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
16 years 1 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...