We describe a hierarchical probabilistic model for the detection and recognition of objects in cluttered, natural scenes. The model is based on a set of parts which describe the e...
Erik B. Sudderth, Antonio B. Torralba, William T. ...
As a network evolves over time, multiple operators modify its configuration, without fully considering what has previously been done. Similar policies are defined more than once, ...
We develop a novel method for class-based feature matching across large changes in viewing conditions. The method (called MBE) is based on the property that when objects share a si...
Abstract. In this paper, feature selection methodology from the machine learning literature is applied to the problem of shape-based classification. This methodology discards stati...
Paul A. Yushkevich, Sarang C. Joshi, Stephen M. Pi...
Traditional 2D DCT implemented by separable 1D transform in horizontal and vertical directions does not take image orientation features in a local window into account. To improve ...