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IDEAL
2005
Springer
14 years 2 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...
ICIP
2007
IEEE
14 years 3 months ago
Estimating Missing Features to Improve Multimedia Retrieval
Retrieval in a multimedia database usually involves combining information from different modalities of data, such as text and images. However, all modalities of the data may not b...
Abraham Bagherjeiran, Nicole S. Love, Chandrika Ka...
CISST
2004
164views Hardware» more  CISST 2004»
13 years 10 months ago
Probabilistic Region Relevance Learning for Content-Based Image Retrieval
Probabilistic feature relevance learning (PFRL) is an effective method for adaptively computing local feature relevance in content-based image retrieval. It computes flexible retr...
Iker Gondra, Douglas R. Heisterkamp
ICPR
2000
IEEE
14 years 9 months ago
A Weighted Distance Approach to Relevance Feedback
Content-based image retrievalsystems use low-levelfeatures like color and texturefor image representation. Given these representationsasfeature vectors, similarity between images ...
Selim Aksoy, Robert M. Haralick, Faouzi Alaya Chei...
DICTA
2008
13 years 10 months ago
Digital Image Retrieval Using Intermediate Semantic Features and Multistep Search
Recently, semantic image retrieval has attracted large amount of interest due to the rapid growth of digital image storage. However, existing approaches have severe limitations. I...
Dengsheng Zhang, Ying Liu, Jin Hou