Combining variable precision rough set and neural network in remote sensing image classification
Qiong Wang, Jian Liu · Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE · 2009
This paper presents a new approach of Remotely Sensed data classification based on Variable Precision Rough set(VPRS) and BP neural network, compared to traditional rough sets, VPRS is more robust to noise and can generate more concise and representative classification rules of the remote sensing image. After the rules are deduced, they are fed to the BP neural network, which results in short training time and a high classification accuracy.