343 search results - page 44 / 69 » Imitation Learning Using Graphical Models |
MLDM
2005
Springer
14 years 1 months ago
2005
Springer
We propose an unsupervised, probabilistic method for learning visual feature hierarchies. Starting from local, low-level features computed at interest point locations, the method c...
AAAI
2007
13 years 10 months ago
2007
Human visual capability has remained largely beyond the reach of engineered systems despite intensive study and considerable progress in problem understanding, algorithms and comp...
CVPR
2008
IEEE
14 years 10 months ago
2008
IEEE
Graphical models such as Bayesian Networks (BNs) are being increasingly applied to various computer vision problems. One bottleneck in using BN is that learning the BN model param...
ICCV
2007
IEEE
14 years 10 months ago
2007
IEEE
We consider the problem of predicting a sequence of real-valued multivariate states from a given measurement sequence. Its typical application in computer vision is the task of mo...
KI
2007
Springer
14 years 2 months ago
2007
Springer
Abstract. Markov logic, as a highly expressive representation formalism that essentially combines the semantics of probabilistic graphical models with the full power of first-orde...