Slope Collapse Detection Method Based on Deep Learning Technology

查看全文 作　　者：Xindai [1]An;Di [1,2]Wu;Xiangwen [1]Xie;Kefeng [1]Song

机构地区：[1]Yellow River Engineering Consulting Co.,Ltd.,Zhengzhou,450003,China;[2]School of Artificial Intelligence and Automation,Huazhong University of Science and Technology,Wuhan,430074,China

出　　处：《Computer Modeling in Engineering & Sciences》索引2023年第2期,共13页

基　　金：supported in part by the National Science Foundation of Guangxi Province under Grant 2021JJA170199;and in part by the Research Project of Yellow River Engineer-ing Consulting with No.2021ky015. 摘　　要：Sofar,slope collapse detectionmainlydepends onmanpower,whichhas the followingdrawbacks:(1)lowreliability,(2)high risk of human safe,(3)high labor cost.To improve the efficiency and reduce the human investment of slope collapse detection,this paper proposes an intelligent detection method based on deep learning technology for the task.In thismethod,we first use the deep learning-based image segmentation technology to find the slope area from the captured scene image.Then the foreground motion detection method is used for detecting the motion of the slope area.Finally,we design a lightweight convolutional neural network with an attentionmechanismto recognize the detected motion object,thus eliminating the interference motion and increasing the detection accuracy rate.Experimental results on the artificial data and relevant scene data show that the proposed detection method can effectively identify the slope collapse,which has its applicative value and brilliant prospect. 关键词：Deep learning slope collapse image segmentation image recognition

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Slope Collapse Detection Method Based on Deep Learning Technology

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