Author:
Hao Shougang,Li Youyang,Wei Jinhong,Cao Tie,Pan Yuhang,Zhou Kejie
Abstract
With the continuous development and expansion of airports, people pay more and more attention to the security of airport boundary. The damage of the boundary is one of the main factors leading to the security of the boundary, so it is very important to develop an automatic detection method of the boundary damage. Based on AlexNet deep learning model, this paper proposes an airport boundary damage detection method. By processing the collected video of the airport boundary, making the boundary damage data set, and then optimizing AlexNet, the experimental results show that compared with the original AlexNet network model, the improved AlexNet network model has shorter training time and significantly improved recognition accuracy, which can effectively identify the boundary damage.
Publisher
Darcy & Roy Press Co. Ltd.
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