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Disentangling rodent behaviors to improve automated behavior recognition

Automated observation and analysis of behavior is important to facilitate progress in many fields of science. Recent developments in deep learning have enabled progress in object detection and tracking, but rodent behavior recognition struggles to exceed 75–80% accuracy for ethologically relevant be...

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Detalles Bibliográficos
Autores principales: Van Dam, Elsbeth A., Noldus, Lucas P. J. J., Van Gerven, Marcel A. J.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10366600/
https://www.ncbi.nlm.nih.gov/pubmed/37496740
http://dx.doi.org/10.3389/fnins.2023.1198209