Schooling machine learning to identify fish -- GCN

The National Oceanic and Atmospheric Administration wants to leverage machine learning to improve its ability to verify marine species. NOAA's Fisheries Sampling Branch is responsible for monitoring and observing fishing in the Northeast and mid-Atlantic. Over the last 25 years, FSB has worked to make this identification easier for its observers -- who started out taking pictures of samples of frozen fish with film cameras, noting the location and focusing on the unique characteristics that allow differentiation of each fish species, such as whole body, gills or fins. The images were submitted within 48 hours and verified by other observers. Currently, images -- which still vary greatly in quality due to different cameras, photographic conditions and characteristics of the species -- are upload to the Fish House, a web-based user interface for a Oracle relational database that is used for species verification.