Due to the difference in resistivity between the garbage and the original soil,the most commonly used garbage soil detection methods are high-density resistivity method and time-domain electromagnetic method.However,the low efficiency of manu-al interpretation of inversion results and the difficulty in ensuring accuracy still need further study.This research introduces the applica-tion of the full convolution neural network in the garbage soil investigation.Through the identification of the garbage soil detection data of the underground buildings of a demolished green space reconstruction project,the garbage soil range was determined,which shows the effectiveness,practicability and reliability of this method.It is the reference basis for waste soil investigation,earthwork cal-culation and improvement of land properties.
关键词
全卷积神经网络/垃圾土/高密度电阻率法/异常识别
Key words
full convolution neural network/garbage soil/high-density resistivity method/abnormal recognition
维普
万方数据