EXAMINATION OF DATA SET IN SETTING OF SEDIMENT DISASTER WARNING AREA USING DEEP LEARNING
In recent years, huge damage with human damage that were caused by abnormal weather phenomena has occurred and it is required to ensure safety. Based on this situation, The Ministry of Land, Infrastructure, Transport and Tourism is setting of sediment disaster warning area as one of the measures. It...
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Veröffentlicht in: | Doboku Gakkai Ronbunshu. F6, Anzen Mondai = Journal of Japan Society of Civil Engineers. Ser. F6, Safety Problem Ser. F6 (Safety Problem), 2019, Vol.75(2), pp.I_177-I_184 |
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Format: | Artikel |
Sprache: | jpn |
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Online-Zugang: | Volltext |
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Zusammenfassung: | In recent years, huge damage with human damage that were caused by abnormal weather phenomena has occurred and it is required to ensure safety. Based on this situation, The Ministry of Land, Infrastructure, Transport and Tourism is setting of sediment disaster warning area as one of the measures. It is required to streamline these works for continuous implementation, because these works are very time-consuming and labor-intensive. In this study, we aimed at automation and efficiency of setting of sediment disaster warning area using deep learning technology that has achieved high results in various fields of image processing. As a result, we were able to estimate with high accuracy the high risk area of damage from sediment disasters, and to show the effectiveness of the proposed method for automation and efficiency. |
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ISSN: | 2185-6621 |
DOI: | 10.2208/jscejsp.75.2_I_177 |