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3DIM
2007
IEEE
14 years 1 months ago
Aerial Lidar Data Classification using AdaBoost
We use the AdaBoost algorithm to classify 3D aerial lidar scattered height data into four categories: road, grass, buildings, and trees. To do so we use five features: height, hei...
Suresh K. Lodha, Darren N. Fitzpatrick, David P. H...
IBPRIA
2007
Springer
14 years 28 days ago
Random Forest for Gene Expression Based Cancer Classification: Overlooked Issues
Random forest is a collection (ensemble) of decision trees. It is a popular ensemble technique in pattern recognition. In this article, we apply random forest for cancer classifica...
Oleg Okun, Helen Priisalu
3DPVT
2006
IEEE
197views Visualization» more  3DPVT 2006»
14 years 24 days ago
Aerial LiDAR Data Classification Using Support Vector Machines (SVM)
We classify 3D aerial LiDAR scattered height data into buildings, trees, roads, and grass using the Support Vector Machine (SVM) algorithm. To do so we use five features: height, ...
Suresh K. Lodha, Edward J. Kreps, David P. Helmbol...
AIRS
2004
Springer
14 years 24 days ago
Effective Topic Distillation with Key Resource Pre-selection
Topic distillation aims at finding key resources which are high-quality pages for certain topics. With analysis in non-content features of key resources, a pre-selection method is ...
Yiqun Liu, Min Zhang, Shaoping Ma
CIKM
2004
Springer
14 years 24 days ago
InfoAnalyzer: a computer-aided tool for building enterprise taxonomies
In this paper we study the problem of collecting training samples for building enterprise taxonomies. We develop a computer-aided tool named InfoAnalyzer, which can effectively as...
Li Zhang, Shixia Liu, Yue Pan, Liping Yang