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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...
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 |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group US
2022
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Materias: | |
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 |
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