Coral Intel is a cutting-edge platform that merges AI and marine science to empower marine researchers, reef managers, and citizen scientists. The goal was not only to improve the performance of coral identification but also to create a tangible, accessible tool for the global community.
Coral Intel is an open-access web application that makes deep learning technology available to users without requiring expertise in machine learning or computer vision. It allows users to upload underwater images or videos and get real-time coral identification results. The platform provides detailed outputs such as bounding boxes, labels (at the genus or species level), and confidence scores for each detection.
The platform bridges the gap between advanced AI and practical field applications. For example, marine ecologists or field scientists can upload survey images without needing to understand the intricacies of model training, essentially relying on Coral Intel as a “virtual coral expert” that can provide instant, reliable identification results.
Coral Intel emphasizes both speed and efficiency, processing batches of images in seconds. This makes it ideal for use in the field. A researcher or scientist on a research vessel can quickly process their reef photos and receive an immediate overview of the coral genera and species detected. This feature can be especially useful for on-the-spot assessments of reef health, allowing rapid identification of dominant species and potential ecological changes.
Coral Intel can identify coral species such as Acropora, Agaricia, Madracis, Meandrina, Mycetophyllia, Oculina, Orbicella, Porites, and Siderastrea and many others, offering crucial data for reef monitoring and conservation.
While Coral Intel delivers high accuracy, its performance depends on the scope of its model training. Currently, the platform excels at identifying Caribbean hard corals in mesophotic imagery, but the accuracy may vary for corals from other regions, such as the Pacific, or in shallow reef environments with different lighting conditions.
To enhance user trust and transparency, the platform allows users to click on each detection to view the model’s confidence score. This openness ensures that users understand when to trust the results and when expert validation may be needed.
Coral Intel is designed to evolve. While the platform is currently focused on identifying Caribbean corals, we actively encourage users to contribute feedback and data from new locations. This continuous flow of user data will help improve the platform through methods like transfer learning. As new data is gathered, the model can be fine-tuned and updated for broader application, including regions with different coral species and lighting conditions.
Coral Intel is not just a tool for identification – it is a dynamic resource that grows with technological advancements and user contributions. The platform will incorporate future updates, including lighter models for edge computing and the ability to identify additional species, such as fish and algae. These updates will make Coral Intel an even more powerful tool for marine research and coral reef conservation.
By merging cutting-edge AI and marine science, Coral Intel provides actionable insights for reef monitoring and conservation. Its evolution will help marine stakeholders, researchers, and conservationists better understand and protect coral ecosystems, providing data-driven insights to ensure ocean sustainability.