In:
IOP Conference Series: Earth and Environmental Science, IOP Publishing, Vol. 571, No. 1 ( 2020-11-01), p. 012073-
Abstract:
Leakage is an important factor affecting the safety of the dam. In the past, manual inspection is a significant way to monitor leakage risk. However, it is time-consuming, inefficient and difficult to quantitative evaluate such as the leakage area. A semantic segmentation method based on the fully convolutional network is proposed to replace the manual inspection for the dam leakage automatic detection. Thirty-eight high-resolution images of dam leakage are collected. FCN-8s and VGG16 backbone are adopted. The results indicated that the FCN-8s achieves the mIoU to 0.59 on the test set, which proves to be an efficient way to detect the dam leakage.
Type of Medium:
Online Resource
ISSN:
1755-1307
,
1755-1315
DOI:
10.1088/1755-1315/571/1/012073
Language:
Unknown
Publisher:
IOP Publishing
Publication Date:
2020
detail.hit.zdb_id:
2434538-6
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