In this work, we explore the use of a learning-based framework for retrieval of relevant mammogram images from a database, for purposes of aiding diagnoses. A fundamental issue is...
Issam El-Naqa, Yongyi Yang, Miles N. Wernick, Niko...
We present an on-line learning framework tailored towards real-time learning from observed user behavior in search engines and other information retrieval systems. In particular, ...
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...
We present an efficient system for video search that maximizes the use of human bandwidth, while at the same time exploiting the machine’s ability to learn in real-time from use...
Alexander G. Hauptmann, Wei-Hao Lin, Rong Yan, Jun...
This paper introduces a composite relevance feedback approach for image retrieval using transaction-based and SVM-based learning. A transaction repository is dynamically constructe...