Evidence map›Paper›PMID 31570119›Full record

ArticleeLife2019

DeepPoseKit, a software toolkit for fast and robust animal pose estimation using deep learning.

Jacob M Graving, Daniel Chae, Hemal Naik, Liang Li, Benjamin Koger, Blair R Costelloe, Iain D Couzin

Open access · goldAbstract read
In one paragraph

Article in eLife, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 225 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
225citing papers in PubMed, 2 pooled it
72.6field-weighted citation impact, top 1% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

225 citing papers in PubMed, 2 syntheses or guidelines pooled it, 548 citations in OpenAlex.

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165 more citing papers are in PubMed but not listed here.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

7 authors at 2 institutions in 2 countries.

Jacob M GravingDepartment of Collective Behaviour, Max Planck Institute of Animal Behavior, Konstanz, Germany.ORCID 0000-0002-5826-467X
Daniel ChaeDepartment of Computer Science, Princeton University, Princeton, United States.
Hemal NaikDepartment of Collective Behaviour, Max Planck Institute of Animal Behavior, Konstanz, Germany.
Liang LiDepartment of Collective Behaviour, Max Planck Institute of Animal Behavior, Konstanz, Germany.ORCID 0000-0002-2447-6295
Benjamin KogerDepartment of Collective Behaviour, Max Planck Institute of Animal Behavior, Konstanz, Germany.
Blair R CostelloeDepartment of Collective Behaviour, Max Planck Institute of Animal Behavior, Konstanz, Germany.ORCID 0000-0001-5291-788X
Iain D CouzinDepartment of Collective Behaviour, Max Planck Institute of Animal Behavior, Konstanz, Germany.ORCID 0000-0001-8556-4558
University of Konstanz · DEPrinceton University · US

Funding

Mobile Health and Treat (mHAT) for Malaria EliminationR21TW010635 · FIC · VANDERBILT UNIVERSITY · PI WRIGHT, DAVID W · 2017 to 2018
$376k
Army Research Office W911NF14-1-0431Army Research Office W911NG-11-1-0385Deutsche Forschungsgemeinschaft DFG Centre of Excellence 2117Horizon 2020 Framework Programme Marie Sklodowska-Curie grant agreement No. 748549Ministry of Science, Research and Art Baden-Württemberg The Strukture-und Innovations fonds fur die Forschung of the State of Baden-WurttembergNational Science Foundation IOS-1355061Nvidia GPU GrantOffice of Naval Research N00014-09-1-1074Office of Naval Research N00014-14-1-0635University of Konstanz Zukunftskolleg Investment Grant
6 · The paper itself

Abstract

Quantitative behavioral measurements are important for answering questions across scientific disciplines-from neuroscience to ecology. State-of-the-art deep-learning methods offer major advances in data quality and detail by allowing researchers to automatically estimate locations of an animal's body parts directly from images or videos. However, currently available animal pose estimation methods have limitations in speed and robustness. Here, we introduce a new easy-to-use software toolkit,

Indexed as

Deep LearningSoftwareAlgorithmsAnimalsBehavior, AnimalComputational BiologyDrosophila melanogasterEquidaeGrasshoppersLocomotiondesert locustD. melanogasterEquus grevyiGrévy's zebraneuroscienceSchistocerca gregaria

Identifiers

PMID31570119
PMCPMC6897514
OpenAlexW2941352015

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.