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ACL
1998
15 years 3 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
GECCO
2009
Springer
204views Optimization» more  GECCO 2009»
15 years 6 months ago
Combined structure and motion extraction from visual data using evolutionary active learning
We present a novel stereo vision modeling framework that generates approximate, yet physically-plausible representations of objects rather than creating accurate models that are c...
Krishnanand N. Kaipa, Josh C. Bongard, Andrew N. M...
ICPR
2006
IEEE
16 years 2 months ago
Hidden Markov Models for Optical Flow Analysis in Crowds
This paper presents an event detector for emergencies in crowds. Assuming a single camera and a dense crowd we rely on optical flow instead of tracking statistics as a feature to ...
Ernesto L. Andrade, Scott Blunsden, Robert B. Fish...
PAMI
2002
149views more  PAMI 2002»
15 years 1 months ago
Region Tracking via Level Set PDEs without Motion Computation
Tracking regions in an image sequence is a challenging and di cult problem in image processing and computer vision, and at the same time, one that has many important applications:...
Abdol-Reza Mansouri
ISMB
2000
15 years 3 months ago
A Probabilistic Learning Approach to Whole-Genome Operon Prediction
We present a computational approach to predicting operons in the genomes of prokaryotic organisms. Our approach uses machine learning methods to induce predictive models for this ...
Mark Craven, David Page, Jude W. Shavlik, Joseph B...