Models of spatial variation in images are central to a large number of low-level computer vision problems including segmentation, registration, and 3D structure detection. Often, i...
— Serious efforts to develop computerized systems for natural language understanding and machine translation have taken place for more than half a century. Some successful system...
—Two probabilistic-based models, namely the Ensemble-Dependent Matrix model [1][3] and the Markov Random Field model [2], have been proposed to deal with faults in nanoscale syst...
Huifei Rao, Jie Chen, Changhong Yu, Woon Tiong Ang...
Facial feature localization is an important research area in both computer vision and pattern analysis. We present in this paper a hierarchical face model. It unifies both the gl...
Algebraic randomization techniques can be applied to hybrid symbolic-numeric algorithms. Here we consider the problem of interpolating a sparse rational function from noisy values...