Active learning has been shown as a key technique for improving content-based image retrieval (CBIR) performance. Among various methods, support vector machine (SVM) active learni...
Steven C. H. Hoi, Rong Jin, Jianke Zhu, Michael R....
The performance of traditional image retrieval approaches remains unsatisfactory, as they are restricted by the wellknown semantic gap and the diversity of textual semantics. To t...
Chuanghua Gui, Jing Liu, Changsheng Xu, Hanqing Lu
Nowadays numerous social images have been emerging on the Web. How to precisely label these images is critical to image retrieval. However, traditional image-level tagging methods...
Yang Yang, Yi Yang, Zi Huang, Heng Tao Shen, Feipi...
We address the challenge of semantic gap reduction for image retrieval through an improved SVM-based active relevance feedback framework, together with a hybrid visual and concept...
This paper examines the problem of image retrieval from large, heterogeneous image databases. We present a technique that fulfills several needs identified by surveying recent res...