For the improvement of iris recognition system performance, the filtering algorithm that picks out counterfeit and noisy data is very important. In this paper, as a part of preproc...
We present a random field based model for stereo vision with explicit occlusion labeling in a probabilistic framework. The model employs non-parametric cost functions that can be ...
We present a discriminative training algorithm, that uses support vector machines (SVMs), to improve the classification of discrete and continuous output probability hidden Markov ...
Statistical learning methods are emerging as a valuable tool for decoding information from neural imaging data. The noisy signal and the limited number of training patterns that ar...
In this paper, we propose a new method called Prototype Ranking (PR) designed for the stock selection problem. PR takes into account the huge size of real-world stock data and app...