We present two machine learning approaches to information extraction from semi-structured documents that can be used if no annotated training data are available, but there does ex...
Active data clustering is a novel technique for clustering of proximity data which utilizes principles from sequential experiment design in order to interleave data generation and...
Abstract This work introduces a self-supervised architecture for robust classification of moving obstacles in urban environments. Our approach presents a hierarchical scheme that r...
Roman Katz, Juan Nieto, Eduardo Mario Nebot, Bertr...
In this paper we present a multi-scale method based on the hybrid notion of rough fuzzy sets, coming from the combination of two models of uncertainty like vagueness by handling r...
For extractive meeting summarization, previous studies have shown performance degradation when using speech recognition transcripts because of the relatively high speech recogniti...