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» User Adaptive Clustering for Large Image Databases
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CVPR
1998
IEEE
15 years 11 months ago
Clustering Appearances of 3D Objects
We introduce a method for unsupervised clustering of images of 3D objects. Our method examines the space of all images and partitions the images into sets that form smooth and par...
Ronen Basri, Dan Roth, David W. Jacobs
PRL
2000
104views more  PRL 2000»
14 years 9 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...
KDD
2012
ACM
220views Data Mining» more  KDD 2012»
12 years 12 months ago
ComSoc: adaptive transfer of user behaviors over composite social network
Accurate prediction of user behaviors is important for many social media applications, including social marketing, personalization and recommendation, etc. A major challenge lies ...
ErHeng Zhong, Wei Fan, Junwei Wang, Lei Xiao, Yong...
CIVR
2009
Springer
583views Image Analysis» more  CIVR 2009»
15 years 9 months ago
Mining from Large Image Sets
So far, most image mining was based on interactive querying. Although such querying will remain important in the future, several applications need image mining at such wide scale...
Luc J. Van Gool, Michael D. Breitenstein, Stephan ...
ICPR
2002
IEEE
15 years 10 months ago
Building a Latent Semantic Index of an Image Database from Patterns of Relevance Feedback
This paper proposes a novel view of the information generated by relevance feedback. Latent semantic analysis is adapted to this view to extract useful inter-query information. Th...
Douglas R. Heisterkamp