ZhiSong Zhang1; LiChun Zhu1; Wei Tang1; XinYi Li1
Source Publication天文和天体物理学研究英文版
AbstractThe Five-hundred-meter Aperture Spherical radio Telescope(FAST) has an active reflector.During observations, the reflector will be deformed into a paraboloid 300 meters in diameter. To improve its surface accuracy, we propose a scheme for photogrammetry to measure the positions of 2226 nodes on the reflector. The way to detect the nodes in the photos is the key problem in this application of photogrammetry. This paper applies a convolutional neural network(CNN) with candidate regions to detect the nodes in the photos. Experimental results show a high recognition rate of 91.5%, which is much higher than the recognition rate for traditional edge detection.
Funding Project[study on the fusion of total station dynamic tracking measuring and IMU inertial measuring for the feed support measurement in FAST] ; [Open Project Program of the Key Laboratory of FAST, NAOC, Chinese Academy of Sciences] ; [Key Laboratory of Radio Astronomy, Chinese Academy of Sciences]
Document Type期刊论文
First Author AffilicationNational Astronomical Observatories, Chinese Academy of Sciences
Recommended Citation
GB/T 7714
ZhiSong Zhang,LiChun Zhu,Wei Tang,et al. unitpanelnodedetectionbycnnonfastreflector[J]. 天文和天体物理学研究英文版,2019,000(001):113.
APA ZhiSong Zhang,LiChun Zhu,Wei Tang,&XinYi Li.(2019).unitpanelnodedetectionbycnnonfastreflector.天文和天体物理学研究英文版,000(001),113.
MLA ZhiSong Zhang,et al."unitpanelnodedetectionbycnnonfastreflector".天文和天体物理学研究英文版 000.001(2019):113.
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