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Title: GitHub - FactoryXCode/DeepLabCut: Official implementation of DeepLabCut: Markerless pose estimation of user-defined features with deep learning for all animals

Open Graph Title: GitHub - FactoryXCode/DeepLabCut: Official implementation of DeepLabCut: Markerless pose estimation of user-defined features with deep learning for all animals

X Title: GitHub - FactoryXCode/DeepLabCut: Official implementation of DeepLabCut: Markerless pose estimation of user-defined features with deep learning for all animals

Description: Official implementation of DeepLabCut: Markerless pose estimation of user-defined features with deep learning for all animals - FactoryXCode/DeepLabCut

Open Graph Description: Official implementation of DeepLabCut: Markerless pose estimation of user-defined features with deep learning for all animals - FactoryXCode/DeepLabCut

X Description: Official implementation of DeepLabCut: Markerless pose estimation of user-defined features with deep learning for all animals - FactoryXCode/DeepLabCut

Opengraph URL: https://github.com/FactoryXCode/DeepLabCut

X: @github

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www.deeplabcut.orghttps://www.mousemotorlab.org/deeplabcut/
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Read a short development and application summary belowhttps://github.com/AlexEMG/DeepLabCut#why-use-deeplabcut
http://DLClive.deeplabcut.orghttp://DLClive.deeplabcut.org
Installation: how to install DeepLabCuthttps://github.com/FactoryXCode/DeepLabCut/blob/master/docs/installation.md
https://github.com/FactoryXCode/DeepLabCut#installation-how-to-install-deeplabcut
herehttps://github.com/DeepLabCut/DeepLabCut/blob/master/conda-environments/README.md#creating-your-own-customized-conda-env-recommended-route-for-linux-ubuntu-centos-mint-etc
Documentation: The DeepLabCut Processhttps://github.com/FactoryXCode/DeepLabCut/blob/master/docs/UseOverviewGuide.md
https://github.com/FactoryXCode/DeepLabCut#documentation-the-deeplabcut-process
Nature Protocols paperhttps://doi.org/10.1038/s41596-019-0176-0
http://DLCcourse.deeplabcut.orghttp://DLCcourse.deeplabcut.org
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DEMO the codehttps://github.com/FactoryXCode/DeepLabCut/blob/master/examples
https://github.com/FactoryXCode/DeepLabCut#demo-the-code
https://github.com/FactoryXCode/DeepLabCut#why-use-deeplabcut
trail trackinghttps://vnmurthylab.org/
reaching in micehttp://www.mousemotorlab.org/
Mathis et al.https://www.nature.com/articles/s41593-018-0209-y
ratshttp://www.mousemotorlab.org/deeplabcut
mouse whiskershttp://www.mousemotorlab.org/deeplabcut
race horseshttp://www.mousemotorlab.org/deeplabcut
Pretraining boosts out-of-domain robustness for pose estimationhttps://arxiv.org/abs/1909.11229
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Mathis et al. 2018https://www.nature.com/articles/s41593-018-0209-y
Mathis/Warrenhttps://www.biorxiv.org/content/early/2018/10/30/457242
Mathis/Warrenhttps://www.biorxiv.org/content/early/2018/10/30/457242
Nath* and Mathis* et al. 2019https://doi.org/10.1038/s41596-019-0176-0
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https://github.com/FactoryXCode/DeepLabCut#code-contributors
Alexander Mathishttps://github.com/AlexEMG
Mackenzie Mathishttps://github.com/MMathisLab
Tanmay Nathhttp://www.mousemotorlab.org/team
Jessy Lauerhttps://github.com/jeylau
DeeperCuthttps://github.com/eldar/pose-tensorflow
contributorshttps://github.com/AlexEMG/DeepLabCut/graphs/contributors
AUTHORShttps://github.com/AlexEMG/DeepLabCut/blob/master/AUTHORS
https://github.com/FactoryXCode/DeepLabCut#community-support-developers--help
https://forum.image.sc/tag/deeplabcut
Scientific Community Image Forum: A discussion forum for scientific image softwarehttps://journals.plos.org/plosbiology/article?id=10.1371/journal.pbio.3000340
https://github.com/DeepLabCut/DeepLabCut/issueshttps://github.com/DeepLabCut/DeepLabCut/issues
https://gitter.im/DeepLabCut/community?utm_source=badge&utm_medium=badge&utm_campaign=pr-badge
here!https://github.com/FactoryXCode/DeepLabCut/blob/master/CONTRIBUTING.md
road maphttps://github.com/FactoryXCode/DeepLabCut/blob/master/docs/roadmap.md
https://github.com/FactoryXCode/DeepLabCut#references
cite Mathis et al, 2018https://www.nature.com/articles/s41593-018-0209-y
Nath, Mathis et al, 2019https://doi.org/10.1038/s41596-019-0176-0
Mathis, Biasi et al. 2020https://arxiv.org/abs/1909.11229
CiteAs.orghttp://citeas.org/
10.1038/s41593-018-0209-yhttps://doi.org/10.1038/s41593-018-0209-y
10.1038/s41596-019-0176-0https://doi.org/10.1038/s41596-019-0176-0
https://github.com/FactoryXCode/DeepLabCut#license
https://github.com/FactoryXCode/DeepLabCut#versions
DeepLabCuthttps://www.nature.com/articles/s41593-018-0209-y
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DeepLabCuthttps://www.nature.com/articles/s41593-018-0209-y
https://github.com/AlexEMG/DeepLabCut/releases/tag/1.11https://github.com/AlexEMG/DeepLabCut/releases/tag/1.11
https://github.com/FactoryXCode/DeepLabCut#news-and-in-the-news
Pretraining boosts out-of-domain robustness for pose estimationhttps://openaccess.thecvf.com/content/WACV2021/papers/Mathis_Pretraining_Boosts_Out-of-Domain_Robustness_for_Pose_Estimation_WACV_2021_paper.pdf
DLClive.deeplabcut.orghttp://DLClive.deeplabcut.org
docshttps://github.com/FactoryXCode/DeepLabCut/blob/master/docs/UseOverviewGuide.md
review on animal pose estimation is published!https://www.sciencedirect.com/science/article/pii/S0959438819301151
Harvard Gazettehttps://news.harvard.edu/gazette/story/newsplus/harvard-researchers-awarded-czi-open-source-award/
CZI's Essential Open Source Software for Science sitehttps://chanzuckerberg.com/eoss/proposals/
Medium posthttps://medium.com/@cziscience/how-open-source-software-contributors-are-accelerating-biomedicine-1a5f50f6846a
releaseshttps://github.com/AlexEMG/DeepLabCut/releases
ImageNet pretraining contributes to robustnesshttps://arxiv.org/abs/1909.11229
review on animal pose estimationhttps://arxiv.org/abs/1909.13868
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https://twitter.com/DeepLabCut
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DLCutilshttps://github.com/AlexEMG/DLCutils
BioRxivhttps://www.biorxiv.org/content/early/2018/10/30/457242
Behavior tracking cuts deephttps://www.nature.com/articles/s41684-018-0164-y
Behavioral Tracking Gets Realhttps://www.nature.com/articles/s41593-018-0215-0
preprinthttps://arxiv.org/abs/1804.03142
Nature Neurosciencehttps://www.nature.com/articles/s41593-018-0209-y
AI Enables Markerless Animal Trackinghttps://news.developer.nvidia.com/ai-enables-markerless-animal-tracking/
Atlantichttps://www.theatlantic.com/science/archive/2018/07/deeplabcut-tracking-animal-movements/564338
arXiv.orghttps://arxiv.org/abs/1804.03142
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