Evaluating Training Parameter Impacts on TransU-Net Performance for UAV-Based Landslide Prediction
Landslides are among the most destructive geological hazards in Malaysia, especially in mountainous and forested areas. Unmanned aerial vehicle (UAV) imagery offers high spatial resolution and flexible data capture, but deep learning performance is highly sensitive to training hyperparameters. In th...
I tiakina i:
| Ngā kaituhi matua: | , , , , , |
|---|---|
| Hōputu: | Artigo |
| Reo: | Inglês |
| I whakaputaina: |
MDPI AG
2026-05-01
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| Rangatū: | Land |
| Ngā marau: | |
| Urunga tuihono: | https://www.mdpi.com/2073-445X/15/6/926 |
| Ngā Tūtohu: |
Kāore He Tūtohu, Me noho koe te mea tuatahi ki te tūtohu i tēnei pūkete!
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