Detection of Water-Bodies Using Semantic Segmentation

被引：0

作者：

Talal, Mina ^{[1
]}

Panthakkan, Alavikunhu ^{[1
]}

Mukhtar, Husameldin ^{[1
]}

Mansoor, Waling ^{[1
]}

Almansoorit, Saeed ^{[2
]}

Al Alunad, Hussain ^{[1
]}

机构：

[1] Univ Dubai, Coll Engn & It, Dubai, U Arab Emirates

[2] MBRSC, Dubai, U Arab Emirates

来源：

2018 INTERNATIONAL CONFERENCE ON SIGNAL PROCESSING AND INFORMATION SECURITY (ICSPIS) | 2018年

关键词：

Deep learning; semantic segmentation; neural network; satellite images; remote sensing;

D O I：

暂无

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

This paper proposes a semantic segmentation technique to automatically detect water-bodies from DubaiSat-2 images. The proposed method uses a deep convolutional neural network transfer-learning model. Several evaluation metrics such as accuracy, precision, and Jaccard coefficient are used to test our proposed algorithm. The overall accuracy for the prediction of water-bodies in DubaiSat-2 image dataset is 99.86%.

引用

页码：77 / 80

页数：4

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