Getting the most out of deep-sea images for ecological assessment

充分利用深海图像进行生态评估

• 批准号: 2401252
• 金额: --
• 依托单位: University of Southampton
• 依托单位国家: 英国
• 项目类别: Studentship
• 财政年份: 2020
• 资助国家: 英国
• 起止时间: 2020 至 无数据
• 项目状态: 已结题
• 来源: https://gtr.ukri.org/projects?ref=studentship-2401252
• 关键词: Getting; most; out; deep; sea

This project will investigate the sensitivity of seabed ecological metrics (e.g. organism density, biomass, diversity indices and community composition) derived from georeferenced imagery to survey design, image quality (e.g. resolution/footprint) and annotation strategies (e.g. human expert vs. state of the art machine learning). Labels generated for both habitat types spanning across multiple image frames and individual organisms within an image frame will be used in the analysis, and the work will establish best practises to optimise the use of image-derived data to monitor communities, both in the UK marine regulatory context and generalizable for further afield.

该项目将调查从地理参考图像得出的海底生态指标（例如生物密度、生物量、多样性指数和群落组成）对勘测设计、图像质量（例如分辨率/足迹）和注释策略（例如人类专家与最先进的机器学习）的敏感性。为跨越多个图像帧和图像帧内的单个生物体的两种栖息地类型生成的标签将用于分析，并且该工作将建立最佳方法来优化使用图像衍生数据来监测社区，无论是在英国海洋监管环境中还是在更远的地方推广。