Automated home-cage behavioral phenotyping of mice
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Automated home-cage behavioral phenotyping of mice
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| Id. |
49267057 |
| Titulo |
Automated home-cage behavioral phenotyping of mice |
| Autor(es) |
Yu, Xinlin
Steele, Andrew D.
Khilnani, Vinita
Garrote, Estibaliz
Jhuang, Hueihan
Serre, Thomas
Poggio, Tomaso
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| Localización |
http://hdl.handle.net/1721.1/49527
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| Versión |
1.0 |
| Estado |
Final
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| Descripción |
We describe a trainable computer vision system enabling the automated analysis of complex mouse behaviors. We provide software and a very large manually annotated video database used for training and testing the system. Our system outperforms leading commercial software and performs on par with human scoring, as measured from the ground-truth manual annotations of thousands of clips of freely behaving animals. We show that the home-cage behavior profiles provided by the system is sufficient to accurately predict the strain identity of individual animals in the case of two standard inbred and two non-standard mouse strains. Our software should complement existing sensor-based automated approaches and help develop an adaptable, comprehensive, high-throughput, fine-grained, automated analysis of rodent behavior.
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| Tipo |
27 p.
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| Palabras clave |
animal monitoring
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| Tipo de Interactividad |
Expositivo
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| Nivel de Interactividad |
muy bajo
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| Audiencia |
Estudiante
Profesor
Autor
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| Estructura |
Atomic |
| Coste |
no
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| Copyright |
sí
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Creative Commons Attribution-Noncommercial 3.0 Unported |
| Formatos |
27 p.
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| Requerimientos técnicos |
Browser: Any
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| Relación |
[References] CBCL-283
[References] MIT-CSAIL-TR-2009-052
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| Fecha de contribución |
04-nov-2009 |
| Contacto |
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