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Intelligent Recognition and Efficient Resource Assessment of Deep-Sea Polymetallic Sulfide Deposits Using Image Enhancement and Semantic Segmentation Strategies

Crossref DOI link: https://doi.org/10.1007/s11053-025-10552-4

Published Online: 2025-08-28

Update policy: https://doi.org/10.1007/springer_crossmark_policy

Authors

Zhao, Qiukui

Yu, Shengyao

Wang, Lintao

Li, Chuanzhi

Li, Chuanshun

Qi, Yu
Funding

Funding for this research was provided by:

National Key Research and Development Program of China (2024YFC2815200)

National Natural Science Foundation of China (42121005)

Taishan Scholars (tstp20231214)

Natural Science Youth Foundation of Shandong Province (ZR2022QD055)

The geological survey projects (DD20242972)
License Information

Text and Data Mining valid from 2025-08-28

Version of Record valid from 2025-08-28
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Article History

Received: 21 January 2025

Accepted: 26 July 2025

First Online: 28 August 2025

Change Date: 6 September 2025

Change Type: Update

Change Details: The Acknowledgments section has been updated

DECLARATIONS

:

: The authors confirm and declare that they have no conflict of interest that could have influenced the work reported in this paper.

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