Infrared Technology, Volume. 45, Issue 6, 663(2023)
Thermal Defect Detection of Composite Insulator Based on One-dimensional Residual Network
[10] [10] HAO R F, LIU C, CHENG Y Q. Application of CNN-1d based on feature fusion in bearing fault diagnosis[C]//2020 Eighth International Conference on Advanced Cloud and Big Data(CBD), 2020: 195-200.
[11] [11] WU X Y, PENG Z K, REN J S, et al. Rub-impact fault diagnosis of rotating machinery based on 1-D convolutional neural networks[J]. IEEE Sensors Journal, 2020, 20(15): 8349-8363.
[14] [14] ZHANG X, ZOU Y, SHI W. Dilated convolution neural network with leaky ReLU for environmental sound classification[C]//2017 22nd International Conference on Digital Signal Processing (DSP), 2017: 1-5.
[15] [15] ZHANG K, SUN M, HAN T X, et al. Residual networks of residual networks: Multilevel residual networks[J]. IEEE Transactions on Circuits and Systems for Video Technology, 2018, 28(6): 1303-1314.
[17] [17] MA X Y, LI D, ZHANG J Y, et al. T-SNE with high order truncation fractional gradient descent method[C]//2020 IEEE 9th Joint International Information Technology and Artificial Intelligence Conference(ITAIC), 2020: 1929-1933.
[18] [18] Gisbrecht A, Schulz A, Hammer B. Parametric nonlinear dimensionality reduction using kernel t-SNE[J]. Neurocomputing, 2015, 147: 71-82.
Get Citation
Copy Citation Text
DONG Yifei, WANG Xiaojie, WANG Renshu, XU Jun, SHU Shengwen, TAO Yiqing. Thermal Defect Detection of Composite Insulator Based on One-dimensional Residual Network[J]. Infrared Technology, 2023, 45(6): 663
Category:
Received: Nov. 8, 2021
Accepted: --
Published Online: Jan. 15, 2024
The Author Email: Shengwen SHU (shushengwen@fzu.edu.cn)
CSTR:32186.14.