Using multiple families of image features is a very efficient strategy to improve performance in object detection or recognition. However, such a strategy induces multiple challenges for machine learning methods, both from a computational and a statistical perspective. The main contribution of this paper is a novel feature sampling procedure dubbed “Tasting” to improve the efficiency of Boostin...

Tabletop displays are a growing area of research for studying social interactions. In this paper, we present TASTI (Tasting and Socializing Tabletop Interface), a novel interaction technique for enhancing tasting events, such as a wine-tasting. Users interact with TASTI’s digital display by manipulating physical objects (such as wine bottles) placed on the table. Each bottle’s position is track...

ABSTRACT Using data deriving from the Paris 1976 blind wine tastings of notable French and American Chardonnays, in the first tasting, and of notable French Bordeaux and American Cabernets in the second tasting, the author discovers the fact that the same 5 of 11 tasters were the most reliable or consistent ones in both wine competitions. He then discusses the very important implications that t...

A bstract We study a simplified model of flavoured Majorana dark matter in the Dark Minimal Flavour Violation framework. The extends Standard Model by flavour triplet and scalar mediator, through which new fermions couple to right-handed up-type quarks. This interaction is governed coupling matrix λ assumed constitute only source CP violation. analyse parameter space this using constraints from...