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126
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ACL
1998
15 years 5 months ago
Feature Lattices for Maximum Entropy Modelling
Maximum entropy framework proved to be expressive and powerful for the statistical language modelling, but it suffers from the computational expensiveness of the model building. T...
Andrei Mikheev
144
Voted
TCSV
2010
14 years 10 months ago
Image and Video Segmentation by Combining Unsupervised Generalized Gaussian Mixture Modeling and Feature Selection
In this letter, we propose a clustering model that efficiently mitigates image and video under/over-segmentation by combining generalized Gaussian mixture modeling and feature sele...
Mohand Saïd Allili, Djemel Ziou, Nizar Bougui...
123
Voted
ICSE
2007
IEEE-ACM
16 years 3 months ago
Feature Oriented Model Driven Development: A Case Study for Portlets
Model Driven Development (MDD) is an emerging paradigm for software construction that uses models to specify programs, and model transformations to synthesize executables. Feature...
Don S. Batory, Oscar Díaz, Salvador Trujill...
CVPR
2007
IEEE
16 years 5 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
132
Voted
ICPR
2006
IEEE
16 years 4 months ago
Exploiting High Dimensional Video Features Using Layered Gaussian Mixture Models
Analysis of video data usually requires training classifiers in high dimensional feature spaces. This paper proposes a layered Gaussian mixture model (LGMM) to exploit high dimens...
Datong Chen, Jie Yang