B-SOiD, an open-source unsupervised algorithm for identification and fast prediction of behaviors
The study of naturalistic behaviour using video tracking is challenging. Here the authors develop a system, B-SOiD which allows automated behavioural tracking and segmentation of video of movements tested in mice, flies and humans.
Guardado en:
Autores principales: | Alexander I. Hsu, Eric A. Yttri |
---|---|
Formato: | article |
Lenguaje: | EN |
Publicado: |
Nature Portfolio
2021
|
Materias: | |
Acceso en línea: | https://doaj.org/article/0959b5bf698845c785607db393069777 |
Etiquetas: |
Agregar Etiqueta
Sin Etiquetas, Sea el primero en etiquetar este registro!
|
Ejemplares similares
-
Unsupervised multi-source domain adaptation with no observable source data.
por: Hyunsik Jeon, et al.
Publicado: (2021) -
Recreation of the periodic table with an unsupervised machine learning algorithm
por: Minoru Kusaba, et al.
Publicado: (2021) -
Improving Unsupervised Domain Adaptive Re-Identification Via Source-Guided Selection of Pseudo-Labeling Hyperparameters
por: Fabian Dubourvieux, et al.
Publicado: (2021) -
Refining the Distributional Inclusion Hypothesis for Unsupervised Hypernym Identification
por: Ludovica Pannitto, et al.
Publicado: (2018) -
Analysis of the mandibular canal course using unsupervised machine learning algorithm.
por: Young Hyun Kim, et al.
Publicado: (2021)