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CVPR
2004
IEEE
14 years 10 months ago
Multiple Bernoulli Relevance Models for Image and Video Annotation
Retrieving images in response to textual queries requires some knowledge of the semantics of the picture. Here, we show how we can do both automatic image annotation and retrieval...
Shaolei Feng, Raghavan Manmatha, Victor Lavrenko
KES
2005
Springer
14 years 2 months ago
Using Relevance Feedback to Learn Both the Distance Measure and the Query in Multimedia Databases
Much of the world’s data is in the form of time series, and many other types of data, such as video, image, and handwriting, can easily be transformed into time series. This fact...
Chotirat (Ann) Ratanamahatana, Eamonn J. Keogh
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...
TKDE
2008
116views more  TKDE 2008»
13 years 8 months ago
Long-Term Cross-Session Relevance Feedback Using Virtual Features
Relevance feedback (RF) is an iterative process, which refines the retrievals by utilizing the user's feedback on previously retrieved results. Traditional RF techniques solel...
Peng-Yeng Yin, Bir Bhanu, Kuang-Cheng Chang, Anlei...
MM
2009
ACM
185views Multimedia» more  MM 2009»
14 years 3 months ago
Deep exploration for experiential image retrieval
Experiential image retrieval systems aim to provide the user with a natural and intuitive search experience. The goal is to empower the user to navigate large collections based on...
Bart Thomee, Mark J. Huiskes, Erwin M. Bakker, Mic...