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This lecture introduces the field of Computational Ethology, focusing on the automated analysis of social behavior in Drosophila Melanogaster. Topics include the use of machine vision and machine learning for behavior measurement, creation of ethograms, challenges in behavioral phenotyping, and the potential advancements in neuroscience. The instructor discusses the benefits, challenges, and future prospects of Computational Ethology, emphasizing the need for interdisciplinary collaboration and advanced data analysis techniques.
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