Successful image reconstruction requires the recognition of a scene and the generation of a clean image of that scene. We propose to use recurrent neural networks for both analysi...
In the field of computer vision feature matching in high dimensional feature spaces is a commonly used technique for object recognition. One major problem is to find an adequate s...
Based on rank-1 update, Sparse Bayesian Learning Algorithm (SBLA) is proposed. SBLA has the advantages of low complexity and high sparseness, being very suitable for large scale pr...
The paper presents a framework for semi-supervised nonlinear embedding methods useful for exploratory analysis and visualization of spatio-temporal network data. The method provid...
Abstract. In this paper we compare two methods for intrinsic dimensionality (ID) estimation based on optimally topology preserving maps (OTPMs). The rst one is a direct approach, w...