LITHOLOGICAL CLASSIFICATION USING MULTI-SENSOR DATA AND CONVOLUTIONAL NEURAL NETWORKS

9 citations as recorded by crossref.

1. Landslide Susceptibility Mapping Using Feature Fusion-Based CPCNN-ML in Lantau Island, Hong Kong Y. Chen et al. 10.1109/JSTARS.2021.3066378
2. Geological Mapping Using Direct Sampling and a Convolutional Neural Network Based on Geochemical Survey Data Z. Wang et al. 10.1007/s11004-022-10023-z
3. Deep learning-based geological map generation using geological routes C. Li et al. 10.1016/j.rse.2024.114214
4. Interpretable Dual-Channel Convolutional Neural Networks for Lithology Identification Based on Multisource Remote Sensing Data S. Wu & Y. Liu 10.3390/rs17071314
5. Pattern Recognition in the Tasks of Landform Mapping S. Kharchenko 10.31857/S2587556623010089
6. Remote Sensing for Lithology Mapping in Vegetation-Covered Regions: Methods, Challenges, and Opportunities Y. Chen et al. 10.3390/min13091153
7. RSWFormer: A Multi-Scale Fusion Network from Local to Global with Multiple Stages for Regional Geological Mapping S. Han et al. 10.3390/rs16142548
8. Lithological Mapping Based on Fully Convolutional Network and Multi-Source Geological Data Z. Wang et al. 10.3390/rs13234860
9. Fusion of GaoFen-5 and Sentinel-2B data for lithological mapping using vision transformer dynamic graph convolutional network Y. Dong et al. 10.1016/j.jag.2024.103780