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facereader fr  (Noldus Information Technology)

 
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    Noldus Information Technology facereader fr
    Facereader Fr, supplied by Noldus Information Technology, used in various techniques. Bioz Stars score: 90/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
    https://www.bioz.com/result/facereader fr/product/Noldus Information Technology
    Average 90 stars, based on 1 article reviews
    facereader fr - by Bioz Stars, 2026-04
    90/100 stars

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    facereader fr  (Noldus Information Technology)
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    Noldus Information Technology facereader fr
    Facereader Fr, supplied by Noldus Information Technology, used in various techniques. Bioz Stars score: 90/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
    https://www.bioz.com/result/facereader fr/product/Noldus Information Technology
    Average 90 stars, based on 1 article reviews
    facereader fr - by Bioz Stars, 2026-04
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    facereader fr version 7.1  (Noldus Information Technology)
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    Note . Action Unit (AU) activity in both datasets was extracted with Noldus <t>FaceReader</t> (FR, Version 7.1). The training process for both datasets was identical: preprocessing, split into 70% training dataset and 30% test dataset, hyperparameter optimization with grouped 10-fold cross-validation in the training dataset. Models trained on each dataset were evaluated twice: once with the 30% hold-out test dataset from the corresponding training dataset and once with 100% of the respective other dataset. The picture for the standardized dataset is model AF33HAS from the KDEF database . The exemplary picture for the unstandardized dataset symbolizes but is not taken from one of our anonymous participants; the model provided written informed consent.
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    facereader software fr version 7.0  (Noldus Information Technology)
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    Noldus Information Technology facereader software fr version 7.0
    Note . Action Unit (AU) activity in both datasets was extracted with Noldus <t>FaceReader</t> (FR, Version 7.1). The training process for both datasets was identical: preprocessing, split into 70% training dataset and 30% test dataset, hyperparameter optimization with grouped 10-fold cross-validation in the training dataset. Models trained on each dataset were evaluated twice: once with the 30% hold-out test dataset from the corresponding training dataset and once with 100% of the respective other dataset. The picture for the standardized dataset is model AF33HAS from the KDEF database . The exemplary picture for the unstandardized dataset symbolizes but is not taken from one of our anonymous participants; the model provided written informed consent.
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    https://www.bioz.com/result/facereader software fr version 7.0/product/Noldus Information Technology
    Average 90 stars, based on 1 article reviews
    facereader software fr version 7.0 - by Bioz Stars, 2026-04
    90/100 stars
    		  Buy from Supplier

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    Note . Action Unit (AU) activity in both datasets was extracted with Noldus FaceReader (FR, Version 7.1). The training process for both datasets was identical: preprocessing, split into 70% training dataset and 30% test dataset, hyperparameter optimization with grouped 10-fold cross-validation in the training dataset. Models trained on each dataset were evaluated twice: once with the 30% hold-out test dataset from the corresponding training dataset and once with 100% of the respective other dataset. The picture for the standardized dataset is model AF33HAS from the KDEF database . The exemplary picture for the unstandardized dataset symbolizes but is not taken from one of our anonymous participants; the model provided written informed consent.

    Journal: PLOS ONE

    Article Title: Training machine learning algorithms for automatic facial coding: The role of emotional facial expressions’ prototypicality

    doi: 10.1371/journal.pone.0281309

    Figure Lengend Snippet: Note . Action Unit (AU) activity in both datasets was extracted with Noldus FaceReader (FR, Version 7.1). The training process for both datasets was identical: preprocessing, split into 70% training dataset and 30% test dataset, hyperparameter optimization with grouped 10-fold cross-validation in the training dataset. Models trained on each dataset were evaluated twice: once with the 30% hold-out test dataset from the corresponding training dataset and once with 100% of the respective other dataset. The picture for the standardized dataset is model AF33HAS from the KDEF database . The exemplary picture for the unstandardized dataset symbolizes but is not taken from one of our anonymous participants; the model provided written informed consent.

    Article Snippet: Both datasets were processed with FaceReader (FR, Version 7.1, Noldus Information Technology) [ ].

    Techniques: Activity Assay, Biomarker Discovery