Joint Multi-scale Convolution Neural Network for Scene Classification of High Resolution Remote Sensing Imagery

Joint Multi-scale Convolution Neural Network for Scene Classification of High Resolution Remote Sensing Imagery

High resolution remote sensing imagery scene classification is important for automatic complex scene recognition, which is the key technology for military and disaster relief, etc. In this paper, we propose a novel joint multi-scale convolution neural network (JMCNN) method using a limited amount of...

Full description

Bibliographic Details
Main Authors: ZHENG Zhuo, FANG Fang, LIU Yuanyuan, GONG Xi, GUO Mingqiang, LUO Zhongwen
Format: Article
Language:zho
Published: Surveying and Mapping Press 2018-05-01
Series:Acta Geodaetica et Cartographica Sinica
Subjects:
high resolution remote sensing imagery
scene classification
joint multi-scale convolution neural network
enhanced high-level feature representation
limit datasets
Online Access:http://html.rhhz.net/CHXB/html/2018-5-620.htm

Internet

http://html.rhhz.net/CHXB/html/2018-5-620.htm

Similar Items