Deep-learning-based identification, tracking, pose estimation and behaviour classification of interacting primates and mice in complex environments
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Marks, Markus
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Jin, Qiuhan
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Sturman, Oliver
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von Ziegler, Lukas
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Kollmorgen, Sepp
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von der Behrens, Wolfger
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Mante, Valerio
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Bohacek, Johannes
dc.contributor.author
Yanik, Mehmet Fatih
dc.date.accessioned
2022-04-25T05:16:53Z
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2022-04-23T15:01:07Z
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2022-04-25T05:16:53Z
dc.date.issued
2022-04
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2522-5839
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10.1038/s42256-022-00477-5
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http://hdl.handle.net/20.500.11850/543464
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10.3929/ethz-b-000543464
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en
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Nature
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dc.title
Deep-learning-based identification, tracking, pose estimation and behaviour classification of interacting primates and mice in complex environments
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Journal Article
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In Copyright - Non-Commercial Use Permitted
dc.date.published
2022-04-21
ethz.journal.title
Nature Machine Intelligence
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4
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4
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Nat Mach Intell
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331
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340
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Engineering brain activity patterns for therapeutics of neuropsychiatric and neurological disorders
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Harnessing novel technologies for precision medicine in pediatric diffuse midline glioma
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Dissecting stress-induced molecular changes in circuits underlying anxiety
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A cross‐disciplinary, data‐driven approach to predict stress resilience from large‐scale behavioral, molecular and neural activity data
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London
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