Correction: Using computer-vision and machine learning to automate facial coding of positive and negative affect intensity.

[This corrects the article DOI: 10.1371/journal.pone.0211735.].

Bibliographic Details
Main Author: PLOS ONE Staff
Format: Article
Language:English
Published: Public Library of Science (PLoS) 2019-01-01
Series:PLoS ONE
Online Access:http://europepmc.org/articles/PMC6405194?pdf=render
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author PLOS ONE Staff
author_facet PLOS ONE Staff
author_sort PLOS ONE Staff
collection DOAJ
description [This corrects the article DOI: 10.1371/journal.pone.0211735.].
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spelling doaj.art-c27eb233f1c44c428f25108bd52e971f2022-12-21T20:03:31ZengPublic Library of Science (PLoS)PLoS ONE1932-62032019-01-01143e021375610.1371/journal.pone.0213756Correction: Using computer-vision and machine learning to automate facial coding of positive and negative affect intensity.PLOS ONE Staff[This corrects the article DOI: 10.1371/journal.pone.0211735.].http://europepmc.org/articles/PMC6405194?pdf=render
spellingShingle PLOS ONE Staff
Correction: Using computer-vision and machine learning to automate facial coding of positive and negative affect intensity.
PLoS ONE
title Correction: Using computer-vision and machine learning to automate facial coding of positive and negative affect intensity.
title_full Correction: Using computer-vision and machine learning to automate facial coding of positive and negative affect intensity.
title_fullStr Correction: Using computer-vision and machine learning to automate facial coding of positive and negative affect intensity.
title_full_unstemmed Correction: Using computer-vision and machine learning to automate facial coding of positive and negative affect intensity.
title_short Correction: Using computer-vision and machine learning to automate facial coding of positive and negative affect intensity.
title_sort correction using computer vision and machine learning to automate facial coding of positive and negative affect intensity
url http://europepmc.org/articles/PMC6405194?pdf=render
work_keys_str_mv AT plosonestaff correctionusingcomputervisionandmachinelearningtoautomatefacialcodingofpositiveandnegativeaffectintensity