[1]GUO Jiawei,LI Yongshu,WANG Hongshu,et al.Seismic Debris Flow Information Detection for High Resolution Images of UAV Based on Transfer Learning[J].Journal of Seismological Research,2018,41(02):180-185.
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Journal of Seismological Research[ISSN 1000-0666/CN 53-1062/P] Volume:
41
Number of periods:
2018 02
Page number:
180-185
Column:
Public date:
2018-04-20
- Title:
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Seismic Debris Flow Information Detection for High Resolution Images of UAV Based on Transfer Learning
- Author(s):
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GUO Jiawei1; 2; LI Yongshu1; WANG Hongshu3; LU Heng4; 5
1 Faculty of Geosciences and Environmental Engineering; Southwest Jiaotong University; Chengdu 611756; Sichuan; China 2 Information Technology Center of
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Chengdu Planning and Management Bureau,Chengdu 610094,Sichuan,China 3 Department of Surveying and Mapping Engineering,Sichuan Water Conservancy Vocational College,Chengdu 611231,Sichuan,China 4 State Key Laboratory of Hydraulics and Mountain River Engineering,Sichuan University,Chengdu 610065,Sichuan,China 5 College of Hydraulic and Hydroelectric Engineering,Sichuan University,Chengdu 610065,Sichuan,China
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- Keywords:
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earthquake; debris flow; UAV high-spatial resolution images; transfer learning; information detection
- CLC:
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P315.9; P642.23
- DOI:
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- Abstract:
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A lot of debris flow disasters(known as the earthquake debris-flow)occurred in post-earthquake,which cause great damage. UAV low-altitude remote sensing technology has the characteristics of convenience,timeliness and so on,and becomes a means of rapid access to disaster information. However,the spectral information of the UAV images is not enough,and it is difficult to detect the information of the earthquake debris flow disaster accurately. Taking into account of the above problems,a method based on transfer learning mechanism for earthquake debris flow detection was proposed. Based on the established earthquake debris flow disaster sample database,features trained by convolution neural network were transferred to earthquake debris flow information detection and the information was detected automatically. The earthquake debris flow information detected based on object-oriented and transfer learning were compared and analyzed. The experimental results showed that the information detection result of earthquake debris flow disaster based on transfer learning was slightly better than that of object-oriented and the former was better than the latter in maintaining smoothness and integrity of earthquake debris flow.