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Underwater archaeology involves the systematic documentation and recovery of information from submerged artifacts, such as pottery amphorae, at underwater sites. Computer vision can significantly aid underwater archaeologists by enabling the automatic detection of these artifacts from images taken underwater by both archaeologists and robots. In this paper, we propose a method for the automatic detection and localization of ancient amphorae in underwater images. Our experimental analysis, conducted on an annotated dataset containing over 1,600 images, demonstrated the effectiveness of the proposed method.

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Automatic Classification and Localization of Ancient Amphorae Through Object Detection in Underwater Archeology

  • 会议论文

  • 发表日期：

    2025年

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  • Lucia Lombardi,
  • Francesco Mercaldo,
  • Antonella Santone

摘要

Underwater archaeology involves the systematic documentation and recovery of information from submerged artifacts, such as pottery amphorae, at underwater sites. Computer vision can significantly aid underwater archaeologists by enabling the automatic detection of these artifacts from images taken underwater by both archaeologists and robots. In this paper, we propose a method for the automatic detection and localization of ancient amphorae in underwater images. Our experimental analysis, conducted on an annotated dataset containing over 1,600 images, demonstrated the effectiveness of the proposed method.