title: PMOT2023: A Large-Scale Multi-Object Tracking (MOT) Dataset with Application to Phytoplankton Observation
abstract: Phytoplankton play a critical role in marine food webs and biogeochemical cycles, and their abundance must be monitored to prevent disasters and improve the marine environment. Although existing algorithms for automatic phytoplankton identification at the image level are available, there are currently no video-level algorithms. This lack of datasets is a significant obstacle to the development of video-level automatic identification algorithms for phytoplankton observations. Deep learning-based 
journal: Journal of Marine Science and Engineering