This paper describes the application of techniques derived from text retrieval research to the content-based querying of image databases. Specically, the use of inverted les, fre...
In relevance feedback algorithms, selective sampling is often used to reduce the cost of labeling and explore the unlabeled data. In this paper, we proposed an active learning alg...
This paper introduces a composite relevance feedback approach for image retrieval using transaction-based and SVM-based learning. A transaction repository is dynamically constructe...
In this paper we present some analysis techniques and indexing strategies aimed to support classification and retrieval of textures using only perceptual features. The goal of thi...
Sebastiano Battiato, Giovanni Gallo, Salvatore Nic...
In this paper, a sub-vector weighting scheme is proposed for the case of small sample in image retrieval with relevance feedback. By partitioning a multi-dimensional visual featur...