Many approaches to object recognition are founded on probability theory, and can be broadly characterized as either generative or discriminative according to whether or not the di...
Preliminary work by the authors made use of the so-called "Manhattan world" assumption about the scene statistics of city and indoor scenes. This assumption stated that ...
In this work, we propose an unsupervised Bayesian model for the detection of moving objects from dynamic scenes. This unsupervised solution is a three-step approach that uses a st...
A robust and automatic system has been developed to detect the visual axis and extract important feature landmarks from slit-lamp photographs, and objectively grade the severity of...
Shaohua Fan, Charles R. Dyer, Larry Hubbard, Barba...
The performance of deep sub-micron designs can be affected by various parametric variations, manufacturing defects, noise or even modeling errors that are all statistical in natur...
Jing-Jia Liou, Kwang-Ting Cheng, Deb Aditya Mukher...