LITHOLOGICAL CLASSIFICATION USING MULTI-SENSOR DATA AND CONVOLUTIONAL NEURAL NETWORKS

15 citations as recorded by crossref.

1. Geological Mapping Using Direct Sampling and a Convolutional Neural Network Based on Geochemical Survey Data Z. Wang et al.
2. Interpretable Dual-Channel Convolutional Neural Networks for Lithology Identification Based on Multisource Remote Sensing Data S. Wu & Y. Liu
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4. Research status and prospect of Ga-rich alunite deposits F. FAN et al.
5. Remote Sensing for Lithology Mapping in Vegetation-Covered Regions: Methods, Challenges, and Opportunities Y. Chen et al.
6. Lithologic Unit Classification Attention-Based and Multiscale Geology Knowledge-Guided Framework in Vegetated Areas Z. Hui et al.
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8. Method of Convolutional Neural Networks for Lithological Classification Using Multisource Remote Sensing Data Z. Zhang et al.
9. Lithological Mapping Based on Fully Convolutional Network and Multi-Source Geological Data Z. Wang et al.
10. Fusion of GaoFen-5 and Sentinel-2B data for lithological mapping using vision transformer dynamic graph convolutional network Y. Dong et al.
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12. Landslide Susceptibility Mapping Using Feature Fusion-Based CPCNN-ML in Lantau Island, Hong Kong Y. Chen et al.
13. Deep learning-based geological map generation using geological routes C. Li et al.
14. Lightweight Deep Learning Approaches for Lithological Mapping in Vegetated Terrains of the Vălioara Valley, Romania V. Árvai & G. Albert
15. Pattern Recognition in the Tasks of Landform Mapping S. Kharchenko