Current approaches to object category recognition require datasets of training images to be manually prepared, with varying degrees of supervision. We present an approach that can...
Robert Fergus, Fei-Fei Li 0002, Pietro Perona, And...
Traditional machine learning makes a basic assumption: the training and test data should be under the same distribution. However, in many cases, this identicaldistribution assumpt...
Transfer learning allows leveraging the knowledge of source domains, available a priori, to help training a classifier for a target domain, where the available data is scarce. Th...
With the increasing interest in metamodeling techniques for Domain Specific Modeling Languages (DSML) definition, there is a strong need to improve the language modeling process. O...
Luis Pedro, Matteo Risoldi, Didier Buchs, Bruno Ba...
This paper describes a new approach to visualization of scenarios within the use case-based engineering of functional requirements – the so-called Video Camera metaphor. The Vid...