FathomNet2023
收藏arXiv2023-07-18 更新2024-08-06 收录
下载链接：
http://arxiv.org/abs/2307.08781v1
下载链接
链接失效反馈官方服务：
资源简介：
FathomNet2023数据集是由蒙特利湾水族馆研究所创建的大规模水下图像数据库，专注于海洋生物的研究和环境监测。该数据集包含5950张训练图像和10744张评估图像，总计23703个本地化标注，主要用于深度学习模型的训练和评估。数据集的创建过程利用了FathomNet的丰富元数据，确保了数据的一致性和质量。该数据集的应用领域包括海洋生态学、生物多样性监测以及新物种的发现，旨在解决海洋生物识别中的分布转移问题。
The FathomNet2023 Dataset is a large-scale underwater image database created by the Monterey Bay Aquarium Research Institute, dedicated to marine biological research and environmental monitoring. It comprises 5950 training images and 10744 evaluation images, with a total of 23703 localized annotations, and is primarily used for the training and evaluation of deep learning models. The dataset construction process leverages the rich metadata of FathomNet to ensure data consistency and quality. Its application areas include marine ecology, biodiversity monitoring and new species discovery, aiming to address the distribution shift problem in marine organism recognition.
提供机构：
蒙特利湾水族馆研究所
创建时间：
2023-07-18
