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» Tackling Large State Spaces in Performance Modelling
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ICCV
2007
IEEE
14 years 10 months ago
Discriminant Embedding for Local Image Descriptors
Invariant feature descriptors such as SIFT and GLOH have been demonstrated to be very robust for image matching and visual recognition. However, such descriptors are generally par...
Gang Hua, Matthew Brown, Simon A. J. Winder
ICC
2007
IEEE
117views Communications» more  ICC 2007»
14 years 3 months ago
Performance Modeling of Multi-Rate HDR and its Effect on TCP Throughput
—An interesting feature of the 3G cellular networks is their ability to support multiple data rates. Though the performance of TCP over wireless networks has been well studied, t...
Wenjing Wang, Shamik Sengupta, Mainak Chatterjee
ROBOCUP
2007
Springer
208views Robotics» more  ROBOCUP 2007»
14 years 2 months ago
3D Tracking by Catadioptric Vision Based on Particle Filters
This paper presents a robust tracking system for autonomous robots equipped with omnidirectional cameras. The proposed method uses a 3D shape and color-based object model. This all...
Matteo Taiana, José António Gaspar, ...
ICML
2008
IEEE
14 years 9 months ago
An object-oriented representation for efficient reinforcement learning
Rich representations in reinforcement learning have been studied for the purpose of enabling generalization and making learning feasible in large state spaces. We introduce Object...
Carlos Diuk, Andre Cohen, Michael L. Littman
ICPR
2002
IEEE
14 years 1 months ago
A Robust Algorithm for Probabilistic Human Recognition From
Human recognition from video requires solving the two tasks, recognition and tracking, simultaneously. This leads to a parameterized time series state space model, representing bo...
Shaohua Kevin Zhou, Rama Chellappa