2033 search results - page 68 / 407 » Semi-Supervised Support Vector Machines |
VLSID
2005
IEEE
14 years 2 months ago
2005
IEEE
The primary advantage of using 3D-FPGA over 2D-FPGA is that the vertical stacking of active layers reduce the Manhattan distance between the components in 3D-FPGA than when placed...
CVBIA
2005
Springer
14 years 2 months ago
2005
Springer
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...
ICANN
2005
Springer
14 years 2 months ago
2005
Springer
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...
IWANN
1999
Springer
14 years 1 months ago
1999
Springer
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...
3DPVT
2006
IEEE
14 years 21 days ago
2006
IEEE
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, ...