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ECML
2004
Springer
13 years 10 months ago
Improving Random Forests
Random forests are one of the most successful ensemble methods which exhibits performance on the level of boosting and support vector machines. The method is fast, robust to noise,...
Marko Robnik-Sikonja
ICIP
2010
IEEE
13 years 2 months ago
Building Emerging Pattern (EP) Random forest for recognition
The Random forest classifier comes to be the working horse for visual recognition community. It predicts the class label of an input data by aggregating the votes of multiple tree...
Liang Wang, Yizhou Wang, Debin Zhao
ICIP
2010
IEEE
13 years 2 months ago
A two-pass random forests classification of airborne lidar and image data on urban scenes
Random forests ensemble classifier showed to be suitable for classifying mutlisource data such as lidar and RGB image for urban scene mapping. However, two major problems remain :...
Li Guo, Nesrine Chehata, Samia Boukir
DMIN
2006
164views Data Mining» more  DMIN 2006»
13 years 6 months ago
Random Forest and PCA for Self-Organizing Maps based Automatic Music Genre Discrimination
Digital music distribution industry has seen a tremendous growth in resent years. Tasks such us automatic music genre discrimination address new and exciting research challenges. A...
Xin Jin, Rongfang Bie
ICCV
2007
IEEE
14 years 6 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