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CVBIA
2005
Springer
15 years 7 months ago
Segmenting Brain Tumors with Conditional Random Fields and Support Vector Machines
Abstract. Markov Random Fields (MRFs) are a popular and wellmotivated model for many medical image processing tasks such as segmentation. Discriminative Random Fields (DRFs), a dis...
Chi-Hoon Lee, Mark Schmidt, Albert Murtha, Aalo Bi...
ICANN
2005
Springer
15 years 7 months ago
Reducing the Effect of Out-Voting Problem in Ensemble Based Incremental Support Vector Machines
Although Support Vector Machines (SVMs) have been successfully applied to solve a large number of classification and regression problems, they suffer from the catastrophic forgetti...
Zeki Erdem, Robi Polikar, Fikret S. Gürgen, N...
IWANN
1999
Springer
15 years 6 months ago
Support Vector Machines for Multi-class Classification
Abstract: Support vector machines (SVMs) are primarily designed for 2-class classification problems. Although in several papers it is mentioned that the combination of K SVMs can b...
Eddy Mayoraz, Ethem Alpaydin
3DPVT
2006
IEEE
197views Visualization» more  3DPVT 2006»
15 years 5 months 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
2006
Springer
15 years 5 months ago
Efficient and Robust Phrase Chunking Using Support Vector Machines
Automatic text chunking is a task which aims to recognize phrase structures in natural language text. It is the key technology of knowledge-based system where phrase structures pro...
Yu-Chieh Wu, Jie-Chi Yang, Yue-Shi Lee, Show-Jane ...