Image retrieval critically relies on the distance function used to compare a query image to images in the database. We suggest to learn such distance functions by training binary ...
One of the difficulties of Content-Based Image Retrieval (CBIR) is the gap between high-level concepts and low-level image features, e.g., color and texture. Relevance feedback wa...
Abstract The effective management and exploitation of multimedia documents requires the extraction of the underlying semantics. Multimedia analysis algorithms can produce fairly ri...
In this paper, we describe an approach for the automatic medical image annotation task of the 2009 CLEF cross-language image retrieval campaign (ImageCLEF). This work is focused o...
The learning-enhanced relevance feedback has been one of the most active research areas in content-based image retrieval in recent years. However, few methods using the relevance ...