Content-based image retrieval can be dramatically improved by providing a good initial database overview to the user. To address this issue, we present in this paper the Adaptive ...
Content-based image retrieval (CBIR) addresses the problem of finding images relevant to the users' information needs, based principally on low-level visual features for whic...
A major problem in the field of content-based image retrieval is the lack of a common performance measure which allows the researcher to compare different image retrieval systems ...
In this paper, we present a new feature extraction method that simultaneously captures the global and local characteristics of an image by adaptively computing hierarchical geomet...
In many vision problems, instead of having fully annotated training data, it is easier to obtain just a subset of data with annotations, because it is less restrictive for the use...
Today's Content-Based Image Retrieval (CBIR) techniques are based on the "k-nearest neighbors" (kNN) model. They retrieve images from a single neighborhood using lo...
Content-Based Image Retrieval (CBIR) is one of the most active research areas in recent years. Many visual feature representations have been explored and many systems built. Howev...