Over the past decade, multiple-instance learning (MIL)
has been successfully utilized to model the localized
content-based image retrieval (CBIR) problem, in which a
bag corresp...
Wu-Jun Li (Hong Kong University of Science and Tec...
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 ...
We propose a new efficient indexing scheme, called the HG-tree, to support content-based retrieval in image databases. Image content is represented by a point in a multidimensional...
A new system, RAIDER (Retrieval and Annotation of Image Databases), has been developed for the management of image databases. RAIDER was designed to combat the inadequacies and in...
A combination of several classifiers using global features for the content description of medical images is proposed. Beside well known texture histogram features, downscaled repr...