Applications of Machine Learning in Marine Ecology Studies

Dear Colleagues,

Recent technological advances in marine sciences enable the collection of large and complex datasets, with multiple interactions between variables, which hampers traditional methods in marine ecology seeking to translate the vast amount of information into a decision-making format. Machine learning methods have the ability to learn from large datasets to find patterns and predict outcomes via unsupervised and supervised learning tasks.

The purpose of this Special Issue is to foster discussions on state-of-the-art machine learning research directions across several areas in marine sciences, including, but not limited to, fisheries, oceanography, pollution, and biodiversity studies. Particular focus will be given to the challenges posed by today's ecological datasets, namely data quality and growing dimensionality. The Special Issue will strengthen the communication channels between marine and machine learning scientists for an efficient use of available data and proper extraction of meaningful information from marine ecology systems.

Dr. Marta Belchior Lopes
Dr. Pedro Reis Costa
Guest Editors

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