DYB-PlanktonNet

DYB-PlanktonNet is a dataset contains marine plankton and suspension particles ROI images recorded from the Daya Bay (DYB), an inner bay of the South China Sea close to Shenzhen City, China. All the images in this dataset were captured by an underwater dark-field imager system called Imaging Plankton Probe (IPP) developed by Dr. Jianping Li’s research group at Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences. The images were labeled through a “human-machine mutually-assisted” process and an “amateur-sorting first, expert-verification follows” strategy to achieve both high annotation efficiency and quality. At present, the dataset has totally 46,804 ROI images in 90 categories, in which 82 are plankton, 7 are suspending particles and 1 is bubbles. The dataset is expected to contribute to the development of automated and intelligent analysis methods for marine plankton and suspending particle images classification and evaluation, hence deepen our understanding of the marine ecosystem.DYB-PlanktonNet 数据集汇集了从位于中国深圳近郊的南海内湾——大亚湾（DYB）所记录的海洋浮游生物和悬浮颗粒的感兴趣区域（ROI）图像。该数据集内的所有图像均由中国科学院深圳先进技术研究院李剑平博士研究团队开发的成像浮游生物探测器（Imaging Plankton Probe，简称IPP）水下暗场成像系统所捕捉。图像标注过程采用“人机协同辅助”以及“初筛业余人员，后经专家验证”的策略，旨在确保标注的高效性与高质量。截至目前，该数据集包含总计 46,804 张 ROI 图像，分为 90 个类别，其中 82 个类别为浮游生物，7 个类别为悬浮颗粒，1 个类别为气泡。此数据集预期将为海洋浮游生物和悬浮颗粒图像的自动分析与智能分类评估方法的发展作出贡献，从而深化我们对海洋生态系统的理解。

搜集汇总

背景与挑战

背景概述

DYB-PlanktonNet是一个专注于海洋浮游生物和悬浮颗粒分类的数据集，包含46,804张ROI图像，分为90个类别。这些图像由中国深圳大亚湾地区通过水下暗场成像系统捕获，并经过CLAHE处理以增强对比度。数据集采用“人机互助”标注策略，旨在支持海洋生态系统的自动化分析。