Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
6856942 | Information Sciences | 2018 | 24 Pages |
Abstract
In an experimental study, we adopt a support vector machine (SVM) classifier as the kernel classifier to obtain the posterior probabilities using dimensionally reduced data. The proposed method is compared with several other methods from various perspectives. Simulation experiments run on several real hyperspectral data sets are reported. The results show that the proposed method performs better than other comparable classification algorithms, especially in a condition-constrained environment.
Keywords
Related Topics
Physical Sciences and Engineering
Computer Science
Artificial Intelligence
Authors
Li Li, Chao Sun, Lianlei Lin, Junbao Li, Shouda Jiang, Jingwei Yin,