A Landslide Intelligent Detection Method based on CNN and RSG_R

Geological disasters not only on the transmission line operation and maintenance are a great threat, but also occurred geological disasters to the people, brings the serious economic loss of property and state government. We propose an algorithm based on depth convolutional neural network (CNN) and an improved region growing algorithm (RSG_R) method for detection of landslide intelligence. The first visible light transmission line inspection image establish landslide detection image data set; and then the CNN of the image data sets were detected, and get the image existence landslide set; finally use rsg_r algorithm to extract the discriminant information of the image elements of disaster disaster (area, boundary and center). The experimental results verify the validity and superiority of the algorithm in two aspects of detection accuracy and sensitivity.