We address evaluation of image understanding and retrieval large scale image data in the context of three evaluation projects. The first project is a comprehensive strategy for e...
Keiji Yanai, Nikhil V. Shirahatti, Prasad Gabbur, ...
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 FIRE, a content-based image retrieval system and the methods we used in the ImageCLEF 2004 evaluation. In FIRE, different features are available to repre...
Methods of retrieving images that incorporate humangenerated metadata, such as keyword annotation and collaborative filtering, are less vulnerable to the semantic gap than content...
Performance evaluation of content-based image retrieval (CBIR) systems is an important but still unsolved problem. The reason for its importance is that only performance evaluatio...