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» Using feature models to automate model transformations
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CVPR
2007
IEEE
16 years 9 months ago
Adaptive Patch Features for Object Class Recognition with Learned Hierarchical Models
We present a hierarchical generative model for object recognition that is constructed by weakly-supervised learning. A key component is a novel, adaptive patch feature whose width...
Fabien Scalzo, Justus H. Piater
PVLDB
2010
89views more  PVLDB 2010»
15 years 5 months ago
Transforming Range Queries To Equivalent Box Queries To Optimize Page Access
Range queries based on L1 distance are a common type of queries in multimedia databases containing feature vectors. We propose a novel approach that transforms the feature space i...
Sakti Pramanik, Alok Watve, Chad R. Meiners, Alex ...
174
Voted
RECOMB
2007
Springer
16 years 7 months ago
A Feature-Based Approach to Modeling Protein-DNA Interactions
Transcription factor (TF) binding to its DNA target site is a fundamental regulatory interaction. The most common model used to represent TF binding specificities is a position spe...
Eilon Sharon, Eran Segal
157
Voted
ICIP
2000
IEEE
16 years 8 months ago
Terrain Feature Identification by Modeling Radar Image Statistics
In this paper we propose a new statistical model for SAR images. According to this model, the SAR image amplitude follows a product of Rayleigh and Bessel functions. We derive the...
Adrian G. Bors, Edwin R. Hancock, Richard C. Wilso...
191
Voted
IJCNN
2008
IEEE
16 years 1 months ago
On the learning of nonlinear visual features from natural images by optimizing response energies
— The operation of V1 simple cells in primates has been traditionally modelled with linear models resembling Gabor filters, whereas the functionality of subsequent visual cortic...
Jussi T. Lindgren, Aapo Hyvärinen