Probabilistic feature relevance learning (PFRL) is an effective method for adaptively computing local feature relevance in content-based image retrieval. It computes flexible retr...
Providing a user with an effective image search engine has been a very active research area. A search by an object model is considered to be one of the most desirable and yet difï...
Abstract. To automatically retrieve documents or images from a database, retrieval systems use similarity measures to compare a request based on features extracted from the documen...
Abstract. This paper presents a novel method of automatic image semantic annotation. Our approach is based on the Image-Keyword Document Model (IKDM) with image features discretiza...
Xiangdong Zhou, Lian Chen, Jianye Ye, Qi Zhang, Ba...
This paper reports our multimedia information retrieval experiments carried out for the ImageCLEF track (ImageCLEFwiki). The task is to answer to user information needs, i.e. quer...