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» Learning Mid-Level Features For Recognition
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AHS
2007
IEEE
219views Hardware» more  AHS 2007»
14 years 3 months ago
A learning machine for resource-limited adaptive hardware
Machine Learning algorithms allow to create highly adaptable systems, since their functionality only depends on the features of the inputs and the coefficients found during the tr...
Davide Anguita, Alessandro Ghio, Stefano Pischiutt...
CVPR
2003
IEEE
14 years 11 months ago
Learning a discriminative classifier using shape context distances
For purpose of object recognition, we learn one discriminative classifier based on one prototype, using shape context distances as the feature vector. From multiple prototypes, th...
Hao Zhang 0003, Jitendra Malik
PR
2007
151views more  PR 2007»
13 years 8 months ago
Learning to display high dynamic range images
In this paper, we present a learning-based image processing technique. We have developed a novel method to map high dynamic range scenes to low dynamic range images for display in...
Guoping Qiu, Jiang Duan, Graham D. Finlayson
CORR
2010
Springer
104views Education» more  CORR 2010»
13 years 9 months ago
Offline Signature Identification by Fusion of Multiple Classifiers using Statistical Learning Theory
This paper uses Support Vector Machines (SVM) to fuse multiple classifiers for an offline signature system. From the signature images, global and local features are extracted and ...
Dakshina Ranjan Kisku, Phalguni Gupta, Jamuna Kant...
CVPR
2011
IEEE
13 years 4 months ago
Supervised Local Subspace Learning for Continuous Head Pose Estimation
Head pose estimation from images has recently attracted much attention in computer vision due to its diverse applications in face recognition, driver monitoring and human computer...
Dong Huang, Markus Storer, Fernando DelaTorre, Hor...