In content-based image retrieval (CBIR), relevant images are identified based on their similarities to query images. Most CBIR algorithms are hindered by the semantic gap between ...
Luo Si, Rong Jin, Steven C. H. Hoi, Michael R. Lyu
An unstructured peer network application was proposed to address the query forwarding problem of distributed search engines and scalability limitations of centralized search engin...
Abstract Compressed domain image retrieval is going to play an increasingly important role in the future. It allows the calculation of image features and hence content-based image ...
We introduce a novel approach to combining rankings from multiple retrieval systems. We use a logistic regression model or an SVM to learn a ranking from pairwise document prefere...
A statistical correlation model for image retrieval is proposed. This model captures the semantic relationships among images in a database from simple statistics of userprovided r...