In this work we introduce a probabilistic model for classifying segmented images. The proposed classifier is very general and it can deal both with images that were segmented wit...
We present a method for the simultaneous detection and segmentation of objects from static images. We employ lowlevel contour features that enable us to learn the coarse object sh...
Contextual information and a priori knowledge play important roles in image segmentation based on neural networks. This paper proposed a method for including contextual information...
We introduce a new perceptron-based discriminative learning algorithm for labeling structured data such as sequences, trees, and graphs. Since it is fully kernelized and uses poin...
In this paper a range synthesis algorithm is proposed as an initial solution to the problem of 3D environment modeling from sparse data. We develop a statistical learning method f...