Penta Classification of Landslide Via Deep Learning Based SegNet and RegNet

Key Points

• This analysis demonstrates effective landslide classification into five categories using deep learning techniques.
• Key evidence shows a high accuracy of 92% when using the RegNet model for segmentation tasks.
• Deep learning methods, including SegNet and RegNet, were applied to process geological images effectively.
• The findings suggest that deep learning models may enhance landslide prediction capabilities for better risk management.