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ICASSP
2007
IEEE
13 years 11 months ago
Integrating Relevance Feedback in Boosting for Content-Based Image Retrieval
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...
Jie Yu, Yijuan Lu, Yuning Xu, Nicu Sebe, Qi Tian
ICPR
2000
IEEE
14 years 5 months ago
Feature Relevance Learning with Query Shifting for Content-Based Image Retrieval
Probabilistic feature relevance learning (PFRL) is an effective technique for adaptively computing local feature relevance for content-based image retrieval. It however becomes le...
Douglas R. Heisterkamp, Jing Peng, H. K. Dai
MICCAI
2007
Springer
14 years 5 months ago
Effectiveness of the Finite Impulse Response Model in Content-Based fMRI Image Retrieval
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...
Bing Bai, Paul B. Kantor, Ali Shokoufandeh
ICPR
2006
IEEE
14 years 5 months ago
Adaptive Discriminant Projection for Content-based Image Retrieval
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...
Jie Yu, Qi Tian
IDEAL
2005
Springer
13 years 10 months ago
Kernel Biased Discriminant Analysis Using Histogram Intersection Kernel for Content-Based Image Retrieval
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...