Acta Optica Sinica, Volume. 38, Issue 7, 0728001(2018)
Airport Detection Method with Improved Region-Based Convolutional Neural Network
An airport detection method based on remote sensing images which combines the cascaded regional proposal network with the detection network is proposed. The regional proposal network is improved to get the airport proposal boxes with a high quality, and the loss function of the detection network is improved to increase the accuracy of the airport detection. In addition, the alternating optimization strategy is adopted to share the convolution layers between the two networks, and thus the airport detection time is greatly shortened. The results show that this proposed method can be used to accurately detect different types of airports under complex backgrounds with a high detection rate, a low false-alarm rate and short average processing time.
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Mingming Zhu, Yuelei Xu, Shiping Ma, Hong Tang, Peng Xin, Hongqiang Ma. Airport Detection Method with Improved Region-Based Convolutional Neural Network[J]. Acta Optica Sinica, 2018, 38(7): 0728001
Category: Remote Sensing and Sensors
Received: Jan. 3, 2018
Accepted: --
Published Online: Sep. 5, 2018
The Author Email: Zhu Mingming (ming_paper@163.com)