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Penta Classification of Landslide Via Deep Learning Based SegNet and RegNet | Synapse
March 3, 2026
Open Access
Penta Classification of Landslide Via Deep Learning Based SegNet and RegNet
CP
C. Pushpalatha
MD
M. Ramya Devi
RR
R. A. Mabel Rose
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Puntos clave
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.
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Cite This Study
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Pushpalatha et al. (Fri,) studied this question.
synapsesocial.com/papers/69a75f1bc6e9836116a2a409
https://doi.org/https://doi.org/10.1007/s44196-025-01114-w