E3S Web Conf.
Volume 233, 20212020 2nd International Academic Exchange Conference on Science and Technology Innovation (IAECST 2020)
|Number of page(s)||4|
|Section||NESEE2020-New Energy Science and Environmental Engineering|
|Published online||27 January 2021|
A Semantic Segmentation Method for Buffer Layer Defect Detection in High Voltage Cable
State Grid Hunan Electric Power Company Limited Research Institute, Changsha 410007, China
a Corresponding author: email@example.com
A semantic segmentation method based on the fully convolutional network is proposed to detect the buffer layer defect in high voltage cable automatically. One hundred seventy-seven high-resolution X-ray images of cables are collected. FCN-8s and VGG16 backbone are adopted. The results indicated that the FCN-8s achieves the mIoU to 0.67 on the test set, proving to be an efficient way to detect the buffer layer defects.
© The Authors, published by EDP Sciences 2021
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