SLEAP: A deep learning system for multi-animal pose tracking

The desire to understand how the brain generates and patterns behavior has driven rapid methodological innovation in tools to quantify natural animal behavior. While advances in deep learning and computer vision have enabled markerless pose estimation in individual animals, extending these to multip...

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Detalles Bibliográficos
Autores principales: Pereira, Talmo D., Tabris, Nathaniel, Matsliah, Arie, Turner, David M., Li, Junyu, Ravindranath, Shruthi, Papadoyannis, Eleni S., Normand, Edna, Deutsch, David S., Wang, Z. Yan, McKenzie-Smith, Grace C., Mitelut, Catalin C., Castro, Marielisa Diez, D’Uva, John, Kislin, Mikhail, Sanes, Dan H., Kocher, Sarah D., Wang, Samuel S.-H., Falkner, Annegret L., Shaevitz, Joshua W., Murthy, Mala
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group US 2022
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9007740/
https://www.ncbi.nlm.nih.gov/pubmed/35379947
http://dx.doi.org/10.1038/s41592-022-01426-1

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9007740/
https://www.ncbi.nlm.nih.gov/pubmed/35379947
http://dx.doi.org/10.1038/s41592-022-01426-1

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