Abstract. This paper explores how to predict query difficulty for contextual image retrieval. We reformulate the problem as the task of predicting how difficult to represent a quer...
* In this paper, we present a study of hierarchically characterizing image content from coarse level to fine level conducted using a series of shape features as a case in point. I...
We present a framework for content based retrieval (CBR) of remotely sensed imagery. The main focus of our research is the segmentation step in CBR. A bank of gabor filters is use...
Active learning methods have been considered with increased interest in the statistical learning community. Initially developed within a classification framework, a lot of extensio...
In Content-based Image Retrieval (CBIR), accurately ranking the returned images is of paramount importance, since users consider mostly the topmost results. The typical ranking st...
Fabio F. Faria, Adriano Veloso, Humberto Mossri de...