Abstract—We propose a probabilistic model for analyzing spatial activation patterns in multiple functional magnetic resonance imaging (fMRI) activation images such as repeated ob...
This paper proposes an approach to classification of adjacent segments of a time series as being either of classes. We use a hierarchical model that consists of a feature extract...
This paper presents a parts-based method for classifying scenes of 3D objects into a set of pre-determined object classes. Working at the part level, as opposed to the whole objec...
Daniel F. Huber, Anuj Kapuria, Raghavendra Donamuk...
We study unsupervised learning of occluding objects in images of visual scenes. The derived learning algorithm is based on a probabilistic generative model which parameterizes obj...
Copyright 2004 IEEE. Published in Conference on Computer Vision and Pattern Recognition (CVPR-2004), June 27 - July 2, 2004, Washington DC. Personal use of this material is permit...