This paper presents a classification-driven biomedical image retrieval system to bride the semantic gap by transforming image features to their global categories at different gran...
Md. Mahmudur Rahman, Sameer Antani, George R. Thom...
Networks have remained a challenge for information retrieval and visualization because of the rich set of tasks that users want to accomplish. This paper n abstract Content-Actor ...
The early success of link-based ranking algorithms was predicated on the assumption that links imply merit of the target pages. However, today many links exist for purposes other ...
Searching for people on the Web is one of the most common query types to the web search engines today. However, when a person name is queried, the returned webpages often contain ...
Dmitri V. Kalashnikov, Rabia Nuray-Turan, Sharad M...
We present an active learning framework to simultaneously learn appearance and contextual models for scene understanding tasks (multi-class classification). Existing multi-class a...