Two Dimensional Hidden Markov Models (2D-HMMs) provide substantial benefits for many computer vision and image analysis applications. Many fundamental image analysis problems, inc...
Mehmet Emre Sargin, Alphan Altinok, Kenneth Rose, ...
In this paper we present a novel method for reducing false positives in breast mass detection. Our approach is based on using the Two-Dimensional Principal Component Analysis (2DPC...
Indexing high dimensional datasets has attracted extensive attention from many researchers in the last decade. Since R-tree type of index structures are known as suffering “curse...
Jiyuan An, Yi-Ping Phoebe Chen, Qinying Xu, Xiaofa...
1 A kernel determines the inductive bias of a learning algorithm on a specific data set, and it is beneficial to design specific kernel for a given data set. In this work, we propo...
Abstract. This paper presents the integration of 3D shape knowledge into a variational model for level set based image segmentation and tracking. Having a 3D surface model of an ob...