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Integrating XMALab and DeepLabCut for high-throughput XROMM
Marker tracking is a major bottleneck in studies involving X-ray reconstruction of moving morphology (XROMM). Here, we tested whether DeepLabCut, a new deep learning package built for markerless tracking, could be applied to videoradiographic data to improve data processing throughput. Our novel wor...
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| Publicado no: | J Exp Biol |
|---|---|
| Main Authors: | , , , , |
| Formato: | Artigo |
| Idioma: | Inglês |
| Publicado em: |
The Company of Biologists Ltd
2020
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| Assuntos: | |
| Acesso em linha: | https://ncbi.nlm.nih.gov/pmc/articles/PMC7490514/ https://ncbi.nlm.nih.gov/pubmed/32665442 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1242/jeb.226720 |
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