滑坡是我国频发的一种自然灾害,往往具有极大的损毁性与危害性,给人们的生命财产安全和生态环境造成严重威胁。滑坡识别对灾后救援及灾后评估有重要意义。针对传统的滑坡识别方法存在识别效率低、主观性强等问题,提出了一种改进的Faster-RCNN滑坡识别方法。该方法在Faster-RCNN模型的基础上,用特征提取能力更为出色的ResNet-50替换了原有的主干网络VGG-16,并引入了感兴趣区域对齐（ROI Align）策略,以提高模型的候选框定位精度,从而进一步提升模型的整体检测效果。实验结果表明,改进后的Faster-RCNN模型在准确率和召回率方面均有所提高,能够快速且准确地检测复杂背景下的滑坡,具有较高的应用价值。

Landslide is a kind of natural disaster that occurs frequently in our country, which is often extremely destructive and hazardous, and poses a serious threat to people's life and property safety and the ecological environment. Landslide identification is important for post-disaster rescue and post-disaster assessment. The traditional landslide identification method has the problems of low identification efficiency and strong subjectivity. In this paper, an improved Faster-RCNN landslide identification method is proposed. Based on the Faster-RCNN model, the method replaces the original backbone network VGG-16 with ResNet-50, which has more excellent feature extraction capability, and introduces the region of interest alignment (ROI Align) strategy to improve the model's candidate frame localization accuracy, so as to further enhance the overall detection effect of the model. The experimental results show that the improved Faster-RCNN model improves both accuracy and recall, and is able to quickly and accurately detect landslides in complex backgrounds, which has high application value.