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The recognition of archaeological and other abandoned mining elements provides an optimal test case for decision-making and management in a broad variety of research fields. A new image dataset was created by obtaining UAV images from different anthropic features. A convolutional neural network architecture was implemented, achieving recognition results of close to 95% accuracy. This methodological approach is suitable for the identification and accurate location of ancient mines and hydrologic infrastructure, providing new tools for accurate mapping of mining landforms. 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