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Automated Qanat Detection: Examining the Application of Deep-Learning in Archaeological Remote Sensing (2018)
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This paper presents the preliminary results of a collaborative project that seeks to develop a deep learning model for automated detection of qanat shafts on CORONA Satellite Imagery. Increasing quantity of air and space-borne imagery available to archaeologists and advances in computational science has created an emerging interest in automated archaeological detection. Previous studies have applied machine learning algorithms for detection of archaeological sites and off-site features, with...