This paper presents novel likelihood estimation to be used for particle filter based object tracking. The likelihood estimation is built upon cascade object detector trained with ...
: This paper addresses the inference of probabilistic classification models using weakly supervised learning. The main contribution of this work is the development of learning meth...
This paper outlines a technique for the automated alignment of digital images of the retina under the assumption that they differ spatially by a geometric global transform. This a...
The objective measurement of blocking artifacts plays an important role in the design, optimization, and assessment of image and video coding systems. We propose a new approach th...
This paper proposes an image compression approach, in which we incorporate primal sketch based learning into the mainstream image compression framework. The key idea of our approa...