Over the past decade, multiple-instance learning (MIL)
has been successfully utilized to model the localized
content-based image retrieval (CBIR) problem, in which a
bag corresp...
Wu-Jun Li (Hong Kong University of Science and Tec...
This paper presents a new relevance feedback method for content-based image retrieval using local image features. This method adopts a genetic programming approach to learn user p...
Jefersson Alex dos Santos, Cristiano D. Ferreira, ...
Multiple Instance Learning (MIL) is a special kind of supervised learning problem that has been studied actively in recent years. We propose an approach based on One-Class Support ...
Content-based image retrieval has become an indispensable tool for managing the rapidly growing collections of digital images. The goal is to organize the contents semantically, a...
Dejan Depalov, Thrasyvoulos N. Pappas, Dongge Li, ...
Relevance feedback (RF) and region-based image retrieval (RBIR) are two widely used methods to enhance the performance of contentbased image retrieval (CBIR) systems. In this paper...