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Vanishing archaeological landscapes in Mesopotamia:CORONA imagery site detection

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Vanishing archaeological landscapes in Mesopotamia:CORONA imagery site detection
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The initial Bing based convolutional network model was retrained using CORONA satellite imagery for the district of Abu Ghraib, west of Baghdad, central Mesopotamian floodplain. First, the detection precision obtained on the area of interest increased sensibly: in particular, the Intersection over Union (IoU) values, at the image segmentation level, surpassed 85 percent, while the general accuracy in detecting archeological sites reached 90 percent. Second, our retrained model allowed the identification of four new sites of archaeological interest (confirmed through field verification), previously not identified by archaeologists with traditional techniques.

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Original publisherarXiv.org
Canonical URLhttps://arxiv.org/abs/2507.13420
Publication timeFri, 24 Jul 2026 02:08:49 +0000
Retrieval time2026-07-24T02:29:49.591Z
Last seen2026-07-24T02:29:49.591Z
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Basis: Derived from the published RSS/Atom feed. Contact: [email protected]. Reviewed: 2026-07-24.

Opening excerpt (first ~120 words) tap to expand

Computer Science > Computer Vision and Pattern Recognition arXiv:2507.13420 (cs) [Submitted on 17 Jul 2025 (v1), last revised 29 Jul 2025 (this version, v2)] Title:AI-ming backwards: Vanishing archaeological landscapes in Mesopotamia and automatic detection of sites on CORONA imagery Authors:Alessandro Pistola, Valentina Orru', Nicolo' Marchetti, Marco Roccetti View a PDF of the paper titled AI-ming backwards: Vanishing archaeological landscapes in Mesopotamia and automatic detection of sites on CORONA imagery, by Alessandro Pistola and 3 other authors View PDF Abstract:By upgrading an existing deep learning model with the knowledge provided by one of the oldest sets of grayscale satellite imagery, known as CORONA, we improved the AI model attitude towards the automatic identification of…

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