This project will use expertise from the cooperative institute for marine and atmospheric research to develop and conduct research that support advancing electronic monitoring capabilities for pacific…

This project will use expertise from the cooperative institute for marine and atmospheric research to develop and conduct research that support advancing electronic monitoring capabilities for pacific fisheries by testing cloudbased storage and evaluating electronic monitoring software to optimize machine learning model integration. One aspect of current electronic monitoring research focuses on how to minimize the costs and time of human video review by exploring artificial intelligence techniques. Cooperative institute staff have developed machine learning models to detect fish and sea turtles on deck and in water. This proposal is focused on advancing these machine learning models by augmenting the training dataset with additional annotations to address data gaps, evaluating the efficacy of cloudbased data access and storage solutions, assessing review software, and exploring the application of machine learning models to infer data for automated catch and bycatch detection.