Pre-trained machine learning models for marine optics research and applications.
Our AI model repository will host state-of-the-art machine learning models trained on NOAA's extensive marine optics datasets. These models will enable automated analysis of underwater imagery for research, monitoring, and conservation efforts.
Pre-trained models for identifying and counting fish species in underwater imagery with bounding box annotations.
Models trained to classify coral species, health status, and morphological characteristics from photogrammetric data.
Segmentation models for pixel-level classification of benthic habitats and detailed ecosystem mapping.
Automated tools for calculating benthic cover percentages and monitoring ecosystem changes over time.
Models for evaluating image quality, clarity, and suitability for scientific analysis and annotation.
Optimized models for deployment in field conditions and real-time analysis of underwater survey data.
First release of pre-trained coral identification model trained on Pacific reef systems.
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Centralized model repository with REST API for integration into research workflows.
Interested in early access to our AI models? Contact the NOAA Optics SI team to learn about collaboration opportunities.