In this paper, we address the question of what kind of knowledge is generally transferable from unlabeled text. We suggest and analyze the semantic correlation of words as a gener...
Never before in history data has been generated at such high volumes as it is today. Exploring and analyzing the vast volumes of data becomes increasingly difficult. Information vi...
Abstract: This paper presents a novel approach for object classification and pose estimation which employs spherical light field rendering to generate virtual views based on synthe...
This work presents a technique of convincingly claiming ownership rights over a trajectory dataset. The presented methodology distorts imperceptibly a collection of sequences, effe...
In this paper a novel complex classifier architecture is proposed. The architecture has a hierarchical tree-like structure with simple artificial neural networks (ANNs) at each no...