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» Algorithms for Large, Sparse Network Alignment Problems
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131
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ICCV
2009
IEEE
15 years 12 days ago
Fast realistic multi-action recognition using mined dense spatio-temporal features
Within the field of action recognition, features and descriptors are often engineered to be sparse and invariant to transformation. While sparsity makes the problem tractable, it ...
Andrew Gilbert, John Illingworth, Richard Bowden
169
Voted
CVPR
2011
IEEE
14 years 11 months ago
Camera Calibration with Lens Distortion from Low-rank Textures
We present a simple, accurate, and flexible method to calibrate intrinsic parameters of a camera together with (possibly significant) lens distortion. This new method can work u...
Zhengdong Zhang, Yasuyuki Matsushita, Yi Ma
ADHOC
2007
101views more  ADHOC 2007»
15 years 2 months ago
Searching strategies for target discovery in wireless networks
— In this paper, we address a fundamental problem concerning the optimal searching strategy in terms of searching cost for the target discovery problem in wireless networks. In o...
Zhao Cheng, Wendi B. Heinzelman
134
Voted
SWARM
2010
SPRINGER
283views Optimization» more  SWARM 2010»
15 years 1 months ago
Principles and applications of swarm intelligence for adaptive routing in telecommunications networks
In the past few years there has been a lot of research on the application of swarm intelligence to the problem of adaptive routing in telecommunications networks. A large number of...
Frederick Ducatelle, Gianni A. Di Caro, Luca Maria...
ICML
2007
IEEE
16 years 3 months ago
Conditional random fields for multi-agent reinforcement learning
Conditional random fields (CRFs) are graphical models for modeling the probability of labels given the observations. They have traditionally been trained with using a set of obser...
Xinhua Zhang, Douglas Aberdeen, S. V. N. Vishwanat...