Flowcam phytoplankton identification service uses a deep learning image recognition algorithm based on a Convolutional Neural Network (CNN) on Flowcam image data residing in the institute’s internal MongoDB database for the phytoplankton taxonomy. The output data has FAIRness characteristics following the Darwin Core standards and relevant vocabularies. With an operational environment in the iMagine-AI platform for processing images and storing the output data along with relevant guidance and documentation material, the service is available for users. Long-term (>4y) high-quality phytoplankton image datasets are also available for exploitation.
The service allows the processing of FlowCam images to determine the taxonomic composition of phytoplankton samples. The service includes setting up an operational environment for users to reuse pre-trained models, refining the AI tools for taxonomic identification, and improving the FAIRness of the full image library data as well as sampled training sets.
