Many content-based image retrieval applications suffer from small sample set and high dimensionality problems. Relevance feedback is often used to alleviate those problems. In thi...
Probabilistic feature relevance learning (PFRL) is an effective technique for adaptively computing local feature relevance for content-based image retrieval. It however becomes le...
The thresholded t-map produced by the General Linear Model (GLM) gives an effective summary of activation patterns in functional brain images and is widely used for feature selecti...
Content-based Image Retrieval (CBIR) is a computer vision application that aims at automatically retrieving images based on their visual content. Linear Discriminat Analysis and i...
It is known that no single descriptor is powerful enough to encompass all aspects of image content, i.e. each feature extraction method has its own view of the image content. A pos...
Lin Mei, Gerd Brunner, Lokesh Setia, Hans Burkhard...