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» Statistical Shape Features in Content-Based Image Retrieval
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BMVC
2001
13 years 10 months ago
Recognition and retrieval via histogram trees
This paper explores a new method for analysing and comparing image histograms. The technique amounts to a novel way of backprojecting an image into one with fewer, statistically s...
Stuart Gibson, Richard Harvey
CLEF
2009
Springer
13 years 6 months ago
Medical Image Retrieval: ISSR at CLEF 2009
This paper represents the first participation of the Institute of Statistical Studies and Research at Cairo University group in CLEF 2009-Medical image retrieval track. Our system...
Waleed Arafa, Ragia Ibrahim
PRL
2000
104views more  PRL 2000»
13 years 7 months ago
PicSOM - content-based image retrieval with self-organizing maps
We have developed a novel system for content-based image retrieval in large, unannotated databases. The system is called PicSOM, and it is based on tree structured self-organizing...
Jorma Laaksonen, Markus Koskela, Sami Laakso, Erkk...
ECCV
2002
Springer
14 years 10 months ago
Learning Shape from Defocus
We present a novel method for inferring three-dimensional shape from a collection of defocused images. It is based on the observation that defocused images are the null-space of ce...
Paolo Favaro, Stefano Soatto
ICCV
2007
IEEE
14 years 10 months ago
How Good are Local Features for Classes of Geometric Objects
Recent work in object categorization often uses local image descriptors such as SIFT to learn and detect object categories. Such descriptors explicitly code local appearance and h...
Michael Stark, Bernt Schiele