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» Using feature models to automate model transformations
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CVPR
2007
IEEE
16 years 8 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 ...
RECOMB
2007
Springer
16 years 6 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
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...
IJCNN
2008
IEEE
16 years 29 days 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