1. Improved SSD‐based transmission tower detection in SAR images
- Author
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Wei Yang, Gao Yuan, Chunsheng Li, and Fei Zou
- Subjects
Synthetic aperture radar ,Computer science ,improved ssd-based transmission tower detection method ,convolutional neural network ,Energy Engineering and Power Technology ,Maintenance engineering ,Convolutional neural network ,transmission system monitoring ,convolutional neural nets ,Radar imaging ,Computer vision ,shallow feature ,object detection method ,Transmission tower ,deep learning-based technique ,business.industry ,General Engineering ,radar computing ,object detection ,sar transmission tower detection ,poles and towers ,Object detection ,transmission system maintenance ,radar imaging ,sar images ,lcsh:TA1-2040 ,learning (artificial intelligence) ,Artificial intelligence ,maintenance engineering ,lcsh:Engineering (General). Civil engineering (General) ,business ,Software ,synthetic aperture radar - Abstract
SAR transmission tower detection is essential to transmission system monitoring and maintenance. Various methods have been proposed to detect transmission tower by using shallow feature. With the development of the deep learning based on convolutional neural network, this study proposed an improved SSD-based transmission tower detection method by introducing deep learning-based technique. First, SSD, a state-of-the-art object detection method, is analysed in detail. Then, the algorithm is modified to fit authors’ specific domain. According to the experiment results in real SAR images, it is showed that the modified method gains better detection performance. Finally, ablation experiments are also performed to confirm each modification step produces better result.
- Published
- 2019
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