Literature DB >> 30845204

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

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Abstract

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

Year:  2019        PMID: 30845204      PMCID: PMC6405194          DOI: 10.1371/journal.pone.0213756

Source DB:  PubMed          Journal:  PLoS One        ISSN: 1932-6203            Impact factor:   3.240


There are errors in the Funding statement. The publisher apologizes for the errors. The correct Funding statement is as follows: This research was supported by the Basic Science Research Program through the National Research Foundation of Korea (NRF) funded by the Ministry of Science, ICT, & Future Planning (2018R1C1B3007313).
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1.  Using computer-vision and machine learning to automate facial coding of positive and negative affect intensity.

Authors:  Nathaniel Haines; Matthew W Southward; Jennifer S Cheavens; Theodore Beauchaine; Woo-Young Ahn
Journal:  PLoS One       Date:  2019-02-05       Impact factor: 3.240

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1.  Automated Detection of Enhanced DBS Device Settings.

Authors:  Yaohan Ding; Itir Onal Ertugrul; Ali Darzi; Nicole Provenza; László A Jeni; David Borton; Wayne Goodman; Jeffrey Cohn
Journal:  Companion Publ 2020 Int Conf Multimodal Interact       Date:  2020-10
  1 in total

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