声纳
水下
计算机科学
侧扫声纳
可靠性(半导体)
海洋工程
实时计算
人工智能
计算机视觉
工程类
地质学
海洋学
功率(物理)
物理
量子力学
作者
Nuno Pessanha Santos,Ricardo Moura,Gonçalo Sampaio Torgal,Victor Lobo,Miguel de Castro Neto
出处
期刊:Data in Brief
[Elsevier]
日期:2024-02-01
卷期号:53: 110132-110132
被引量:3
标识
DOI:10.1016/j.dib.2024.110132
摘要
Unmanned vehicles have become increasingly popular in the underwater domain in the last decade, as they provide better operation reliability by minimizing human involvement in most tasks. Perception of the environment is crucial for safety and other tasks, such as guidance and trajectory control, mainly when operating underwater. Mine detection is one of the riskiest operations since it involves systems that can easily damage vehicles and endanger human lives if manned. Automating mine detection from side-scan sonar images enhances safety while reducing false negatives. The collected dataset contains 1170 real sonar images taken between 2010 and 2021 using a Teledyne Marine
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