We describe a neurally-inspired, unsupervised learning algorithm that builds a non-linear generative model for pairs of face images from the same individual. Individuals are then ...
We propose a novel, non-simulative, probabilistic model for switching activity in sequential circuits, capturing both spatio-temporal correlations at internal nodes and higher ord...
Sanjukta Bhanja, Karthikeyan Lingasubramanian, N. ...
Cast shadows induced by moving objects often cause serious problems to many vision applications. We present in this paper an online statistical learning approach to model the backg...
Background: Predicting the suppression activity of antisense oligonucleotide sequences is the main goal of the rational design of nucleic acids. To create an effective predictive ...
This paper investigates novel LBP-guided active contour approaches to texture segmentation. The Local Binary Pattern (LBP) operator is well suited for texture representation, comb...
Michalis A. Savelonas, Dimitrios K. Iakovidis, Dim...