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» Learning the Relative Importance of Features in Image Data
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106
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CVPR
2005
IEEE
16 years 5 months ago
Discriminative Training for Object Recognition Using Image Patches
We present a method for automatically learning discriminative image patches for the recognition of given object classes. The approach applies discriminative training of log-linear...
Thomas Deselaers, Daniel Keysers, Hermann Ney
3DPVT
2006
IEEE
247views Visualization» more  3DPVT 2006»
15 years 7 months ago
Contour-Based Object Detection in Range Images
This paper presents a novel object recognition approach based on range images. Due to its insensitivity to illumination, range data is well suited for reliable silhouette extracti...
Stefan Stiene, Kai Lingemann, Andreas Nüchter...
IJCNN
2006
IEEE
15 years 10 months ago
Combining Multi-Frame Images for Enhancement Using Self-Delaying Dynamic Networks
Abstract— This paper presents the use of a newly created network structure known as a Self-Delaying Dynamic Network (SDN). The SDNs were created to process data which varies with...
Lewis Eric Hibell, Honghai Liu, David J. Brown
TMI
2011
147views more  TMI 2011»
14 years 10 months ago
Labeling of Lumbar Discs Using Both Pixel- and Object-Level Features With a Two-Level Probabilistic Model
Abstract—Backbone anatomical structure detection and labeling is a necessary step for various analysis tasks of the vertebral column. Appearance, shape and geometry measurements ...
Raja' S. Alomari, Jason J. Corso, Vipin Chaudhary
RECOMB
2007
Springer
16 years 4 months ago
Learning Gene Regulatory Networks via Globally Regularized Risk Minimization
Learning the structure of a gene regulatory network from time-series gene expression data is a significant challenge. Most approaches proposed in the literature to date attempt to ...
Yuhong Guo, Dale Schuurmans