Semantic-based image retrieval has attracted great interest in recent years. This paper proposes a region-based image retrieval system with high-level semantic learning. The key f...
Popular image retrieval schemes generally rely only on a single mode, (either low level visual features or embedded text) for searching in multimedia databases. Many popular image...
In image retrieval, most existing approaches that incorporate local features produce high dimensional vectors, which lead to a high computational and data storage cost. Moreover, ...
Image segmentation is not only hard and unnecessary for texture-based image retrieval, but can even be harmful. Images of either individual or multiple textures are best described...
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 ...