Getting Started

MERMAID Collect offers an integrated AI-assisted image classification developed in collaboration with CoralNet, the leading platform for automated benthic image analysis. The Image classification model is designed to streamline and standardize the processing of benthic photo quadrats. This tool allows users to upload entire transects, apply automatic point-based classification using a pre-trained model, and interactively review results—all within an easy-to-use and efficient workflow from your project in MERMAID Collect.

Each photo is classified using a fixed grid of 25 points and a standardized set of benthic attribute labels. These labels include both high-level benthic attributes (e.g., Hard coral or Macroalgae) and specific coral genera and growth forms (e.g., Acropora branching). This approach supports data comparability across datasets and projects within MERMAID.

While the AI provides an efficient initial classification, all point classifications must be reviewed and confirmed by a trained observer. This includes verifying model-classified benthic attribute labels and manually classifying any unclassified points. This review step is essential to ensure the accuracy and reliability of submitted data.

Please note: The current AI image classification model is a beta version, undergoing testing and user feedback integration. It will be optimized in a future release to improve classification performance and expand the range of benthic attributes and coral growth forms that can be detected. Users are encouraged to report performance issues or classification inaccuracies to support ongoing model improvement by contacting us at contact@datamermaid.org.