ATTENTION-BASED CONVOLUTIONAL NEURAL NETWORK FOR THE DETECTION OF BUILT-UP AREAS IN HIGH-RESOLUTION SAR IMAGES

被引：0
|
作者：
Wu, Yunfei [1 ]
Zhang, Rong
Zhan, Yibing
机构：
[1] USTC, Dept Elect Engn & Informat Sci, Hefei 230027, Anhui, Peoples R China
来源：
IGARSS 2018 - 2018 IEEE INTERNATIONAL GEOSCIENCE AND REMOTE SENSING SYMPOSIUM | 2018年
关键词：
high-resolution SAR images; built-up areas; neural networks; attention;
D O I：
暂无
中图分类号：
TM [电工技术]; TN [电子技术、通信技术];
学科分类号：
0808 ; 0809 ;
摘要：
The detection of built-up areas is essential for high-resolution Synthetic Aperture Rader (SAR) applications, such as urban planning and environmental monitoring. In this paper, we proposed an attention based convolutional neural network for the detection of built-up areas in SAR images. Our network composes of two parts. First part contains two branches, one is designed to obtain high detection rate and the other one is designed to obtain low false alarm rate. Second part aims to merge the advantages of the two detection results of first part by using attention mechanism. Experiments on TerraSAR-X high resolution SAR images over Beijing demonstrate the effectiveness of proposed method.
引用
收藏
页码：4495 / 4498
页数：4
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