In this paper an unsupervised scheme for stereoscopic video object extraction is presented based on a neural network classifier. More particularly, the procedure includes: (A) A retraining algorithm for adapting neural network weights to current conditions and (B) An active contour module, which extracts the retraining set. The retraining algorithm takes into consideration both the former and t...

This paper addresses the problem of semi-supervised classification on document collections using retraining (also called self-training). A possible application is focused Web crawling which may start with very few, manually selected, training documents but can be enhanced by automatically adding initially unlabeled, positively classifiedWeb pages for retraining. Such an approach is by itself no...

In this paper, we report our investigations on the use of adaptation and retraining in our bilingual (Italian, German) and multidialectal recognition system. Our approach for bilingual speech recognition is to assume the two languages as being one, which is best suited for a task where Italian and German natives speak both languages, resulting in a variety of accents and dialects. We performed ...

In vocational retraining centres, a test battery including several performance tests is generally administered to assess the occupational aptitude of rehabilitants and to predict their success in occupational retraining. This paper presents the multiple regressions of a set of achievement scores on "grades of retraining" and "grades of final examination", respectively, concerning retraining to ...