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Deep Learning in Archaeological Remote Sensing: Automated Qanat Detection in the Kurdistan Region of Iraq
2020
Remote Sensing
In this paper, we report the results of our work on automated detection of qanat shafts on the Cold War-era CORONA Satellite Imagery. The increasing quantity of air and space-borne imagery available to archaeologists and the advances in computational science have created an emerging interest in automated archaeological detection. Traditional pattern recognition methods proved to have limited applicability for archaeological prospection, for a variety of reasons, including a high rate of false
doi:10.3390/rs12030500
fatcat:l2rkex4lnva37aq3j64gxdirki