A novel USF-Net approach for open-pit mine extraction: integrating SAM model with task-specific adaptation

Kai Sun; Yaru Zhao; Yawei Li; Yuzhi Wang; Min Ji; Yujuan Zhang; Yi Zhang

doi:10.1117/12.3059139

2 January 2025 A novel USF-Net approach for open-pit mine extraction: integrating SAM model with task-specific adaptation

Kai Sun, Yaru Zhao, Yawei Li, Yuzhi Wang, Min Ji, Yujuan Zhang, Yi Zhang

Author Affiliations +

Proceedings Volume 13514, International Conference on Remote Sensing and Digital Earth (RSDE 2024); 1351404 (2025) https://doi.org/10.1117/12.3059139
Event: 2024 International Conference on Remote Sensing and Digital Earth, 2024, Chengdu, China

Abstract

As the demand for mineral raw materials continues to grow, the frequency of mining has increased year by year. Quickly and accurately identifying mining boundaries has become one of the core issues in mining management. Aiming at the problems of complex feature scenes and ambiguous boundary features in open pit mining areas, this paper proposes an innovative USF-Net method, which combines SAM with task-specific knowledge to effectively improve the recognition accuracy of open pit mining boundaries. By merging the generic knowledge from the SAM model with the specific requirements of the open pit mine extraction task, the method demonstrates excellent performance in complex mining scenarios. The experimental results show that USF-Net has high robustness and accuracy in open pit mining area boundary identification, which provides a new technical idea for open pit mining management.

(2025) Published by SPIE. Downloading of the abstract is permitted for personal use only.

Citation Download Citation

Kai Sun, Yaru Zhao, Yawei Li, Yuzhi Wang, Min Ji, Yujuan Zhang, and Yi Zhang "A novel USF-Net approach for open-pit mine extraction: integrating SAM model with task-specific adaptation", Proc. SPIE 13514, International Conference on Remote Sensing and Digital Earth (RSDE 2024), 1351404 (2 January 2025); https://doi.org/10.1117/12.3059139

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