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135
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ICCV
2007
IEEE
15 years 11 months ago
Image Classification using Random Forests and Ferns
We explore the problem of classifying images by the object categories they contain in the case of a large number of object categories. To this end we combine three ingredients: (i...
Andrew Zisserman, Anna Bosch, Xavier Muñoz
KDD
2002
ACM
144views Data Mining» more  KDD 2002»
15 years 10 months ago
Efficiently mining frequent trees in a forest
Mining frequent trees is very useful in domains like bioinformatics, web mining, mining semi-structured data, and so on. We formulate the problem of mining (embedded) subtrees in ...
Mohammed Javeed Zaki
84
Voted
PRL
2007
166views more  PRL 2007»
14 years 9 months ago
Boosted Landmarks of Contextual Descriptors and Forest-ECOC: A novel framework to detect and classify objects in cluttered scene
In this paper, we present a novel methodology to detect and recognize objects in cluttered scenes by proposing boosted contextual descriptors of landmarks in a framework of multi-...
Sergio Escalera, Oriol Pujol, Petia Radeva
ICIP
2009
IEEE
14 years 7 months ago
An incremental extremely random forest classifier for online learning and tracking
Decision trees have been widely used for online learning classification. Many approaches usually need large data stream to finish decision trees induction, as show notable limitat...
Aiping Wang, Guowei Wan, Zhiquan Cheng, Sikun Li
VIS
2006
IEEE
90views Visualization» more  VIS 2006»
15 years 11 months ago
Real-Time Illustration of Vascular Structures
Felix Ritter, Christian Hansen, Volker Dicken, ...