Update summarization aims to create a summary over a topic-related multi-document dataset based on the assumption that the user has already read a set of earlier documents of the ...
Context is critical for minimising ambiguity in object de-
tection. In this work, a novel context modelling framework
is proposed without the need of any prior scene segmen-
tat...
This paper examines the problem of image retrieval from large, heterogeneous image databases. We present a technique that fulfills several needs identified by surveying recent res...
Learning-enhanced relevance feedback is one of the most promising and active research directions in recent year's content-based image retrieval. However, the existing approac...
We present a Bayesian framework for content-based image retrieval which models the distribution of color and texture features within sets of related images. Given a userspecified ...