: Despite the efforts to reduce the semantic gap between user perception of similarity and featurebased representation of images, user interaction is essential to improve retrieval...
The performance of many supervised and unsupervised learning algorithms is very sensitive to the choice of an appropriate distance metric. Previous work in metric learning and ada...
Probabilistic feature relevance learning (PFRL) is an effective method for adaptively computing local feature relevance in content-based image retrieval. It computes flexible retr...
In this paper, a new recursive algorithm is proposed for optimal estimation of similarity measure used in a content-based retrieval system. This is performed through a relevance f...
Content-based Image Retrieval (CBIR) is a computer vision application that aims at automatically retrieving images based on their visual content. Linear Discriminat Analysis and i...