A lightweight convolutional neural network with end-to-end learning for three-dimensional mineral prospectivity modeling: A case study of the Sanhetun Area, Heilongjiang Province, Northeastern China

Zhang, Baoyi; Xu, Kun; Khan, Umair; Li, Xuefeng; Du, Linze; Xu, Zhanghao

doi:10.1016/j.oregeorev.2023.105788

Ore Geology Reviews

2023

DOI: 10.1016/j.oregeorev.2023.105788

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A lightweight convolutional neural network with end-to-end learning for three-dimensional mineral prospectivity modeling: A case study of the Sanhetun Area, Heilongjiang Province, Northeastern China

Baoyi Zhang,

Kun Xu,

Umair Khan

et al.

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Cited by 9 publications

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A lightweight convolutional neural network with end-to-end learning for three-dimensional mineral prospectivity modeling: A case study of the Sanhetun Area, Heilongjiang Province, Northeastern China

Cited by 9 publications

References 57 publications

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3D mineral prospectivity modeling using multi-scale 3D convolution neural network and spatial attention approaches

3D mineral prospectivity modeling at the Axi epithermal gold deposit, NW China by using a feature adaptive fusion strategy

CNN-Transformers for mineral prospectivity mapping in the Maodeng–Baiyinchagan area, Southern Great Xing'an Range

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