Bridging the gap in FER: addressing age bias in deep learning | Paper Citation Record

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This paper cites Peekinginsidetheblack-box:Asurveyonexplainableartificialintelligence(xai).

Bridging the gap in FER: addressing age bias in deep learning Peekinginsidetheblack-box:Asurveyonexplainableartificialintelligence(xai)

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This paper cites Fully automated age-weighted expression classification using real and apparent age.

Bridging the gap in FER: addressing age bias in deep learning Fully automated age-weighted expression classification using real and apparent age

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Bridging the gap in FER: addressing age bias in deep learning Unresolved cited work

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This paper cites A review study: The effect of face aging at estimating age and face recognition.

Bridging the gap in FER: addressing age bias in deep learning A review study: The effect of face aging at estimating age and face recognition

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Bridging the gap in FER: addressing age bias in deep learning Explainableartificialintelligence(xai):Concepts,taxonomies,opportunitiesandchallengestowardresponsible ai

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This paper cites A survey of predictive modeling on imbalanced domains.

Bridging the gap in FER: addressing age bias in deep learning A survey of predictive modeling on imbalanced domains

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This paper cites Further evidence on preschoolers’ interpretation of facial expressions.

Bridging the gap in FER: addressing age bias in deep learning Further evidence on preschoolers’ interpretation of facial expressions

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This paper cites Comparisonbetweendeeplearningmodelsandtraditionalmachinelearningapproachesforfacial expressionrecognitioninageingadults.

Bridging the gap in FER: addressing age bias in deep learning Comparisonbetweendeeplearningmodelsandtraditionalmachinelearningapproachesforfacial expressionrecognitioninageingadults

Reference 8

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This paper cites Karolinska directed emotional faces.

Bridging the gap in FER: addressing age bias in deep learning Karolinska directed emotional faces

Reference 9

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Bridging the gap in FER: addressing age bias in deep learning Thedartmouthdatabaseofchildren’sfaces:Acquisitionandvalidationofanewfacestimulus set

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This paper cites The Expression of the Emotions in Man and Animals.

Bridging the gap in FER: addressing age bias in deep learning The Expression of the Emotions in Man and Animals

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This paper cites Demographicbiasinbiometrics:Asurveyonanemergingchallenge.

Bridging the gap in FER: addressing age bias in deep learning Demographicbiasinbiometrics:Asurveyonanemergingchallenge

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This paper cites Fairness through awareness, in: Proceedings of the 3rd Innovations in Theoretical Computer Science Conference, p.

Bridging the gap in FER: addressing age bias in deep learning Fairness through awareness, in: Proceedings of the 3rd Innovations in Theoretical Computer Science Conference, p

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This paper cites Faces-a database of facial expressions in young, middle-aged, and older women and men: Development and validation.

Bridging the gap in FER: addressing age bias in deep learning Faces-a database of facial expressions in young, middle-aged, and older women and men: Development and validation

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Bridging the gap in FER: addressing age bias in deep learning The nimh child emotional faces picture set (nimh-chefs): A new set of children’s facial emotion stimuli

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This paper cites An argument for basic emotions.

Bridging the gap in FER: addressing age bias in deep learning An argument for basic emotions

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This paper cites Facial action coding system : investigator’s guide.

Bridging the gap in FER: addressing age bias in deep learning Facial action coding system : investigator’s guide

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This paper cites Facialageaffectsemotionalexpressiondecoding.

Bridging the gap in FER: addressing age bias in deep learning Facialageaffectsemotionalexpressiondecoding

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This paper cites Deep Learning-Based Facial Expression Recognition for the Elderly: A Systematic Review.

Bridging the gap in FER: addressing age bias in deep learning Deep Learning-Based Facial Expression Recognition for the Elderly: A Systematic Review

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This paper cites Evaluating Facial Expression Recognition Datasets for Deep Learning: A Benchmark Study with Novel Similarity Metrics.

Bridging the gap in FER: addressing age bias in deep learning Evaluating Facial Expression Recognition Datasets for Deep Learning: A Benchmark Study with Novel Similarity Metrics

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This paper cites Unveiling the human-like similarities of automatic facial expression recognition: An empirical exploration through explainable ai.

Bridging the gap in FER: addressing age bias in deep learning Unveiling the human-like similarities of automatic facial expression recognition: An empirical exploration through explainable ai

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This paper cites Le développement de la reconnaissance des expressions faciales des émotions chez l’enfant.

Bridging the gap in FER: addressing age bias in deep learning Le développement de la reconnaissance des expressions faciales des émotions chez l’enfant

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This paper cites Children’sknowledgeoffacialexpressionsofemotions:Distinguishingfearandsurprise.

Bridging the gap in FER: addressing age bias in deep learning Children’sknowledgeoffacialexpressionsofemotions:Distinguishingfearandsurprise

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This paper cites Having difficulties reading the facial expression of older individuals? blame it on the facial muscles, not the wrinkles.

Bridging the gap in FER: addressing age bias in deep learning Having difficulties reading the facial expression of older individuals? blame it on the facial muscles, not the wrinkles

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Bridging the gap in FER: addressing age bias in deep learning Xai—explainable artificial intelligence

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This paper cites Facial expression recognition influenced by human aging.

Bridging the gap in FER: addressing age bias in deep learning Facial expression recognition influenced by human aging

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This paper cites Human age estimation: What is the influence across race and gender?, in: 2010 IEEE Computer Society Conference on Computer Vision and Pattern Recognition - Workshops, pp.

Bridging the gap in FER: addressing age bias in deep learning Human age estimation: What is the influence across race and gender?, in: 2010 IEEE Computer Society Conference on Computer Vision and Pattern Recognition - Workshops, pp

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This paper cites Deep residual learning for image recognition, in: 2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR), pp.

Bridging the gap in FER: addressing age bias in deep learning Deep residual learning for image recognition, in: 2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR), pp

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Bridging the gap in FER: addressing age bias in deep learning Searchingformobilenetv3,in:2019IEEE/CVFInternationalConferenceonComputerVision(ICCV),pp.1314–1324

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Bridging the gap in FER: addressing age bias in deep learning MobileNets: Efficient Convolutional Neural Networks for Mobile Vision Applications

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This paper cites Facial expression recognition with age-group expression feature learning, in: 2024 International Joint Conference on Neural Networks (IJCNN), pp.

Bridging the gap in FER: addressing age bias in deep learning Facial expression recognition with age-group expression feature learning, in: 2024 International Joint Conference on Neural Networks (IJCNN), pp

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This paper cites Bringinganecologicalperspectivetothestudyofagingandrecognitionofemotionalfacialexpressions: Past, current, and future methods.

Bridging the gap in FER: addressing age bias in deep learning Bringinganecologicalperspectivetothestudyofagingandrecognitionofemotionalfacialexpressions: Past, current, and future methods

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This paper cites Expression recognition across age, in: 2021 16th IEEE International Conference on Automatic Face and Gesture Recognition (FG 2021), pp.

Bridging the gap in FER: addressing age bias in deep learning Expression recognition across age, in: 2021 16th IEEE International Conference on Automatic Face and Gesture Recognition (FG 2021), pp

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This paper cites Ultralytics yolo.

Bridging the gap in FER: addressing age bias in deep learning Ultralytics yolo

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Bridging the gap in FER: addressing age bias in deep learning Unresolved cited work

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This paper cites Changes in computer-analyzed facial expressions with age.

Bridging the gap in FER: addressing age bias in deep learning Changes in computer-analyzed facial expressions with age

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This paper cites Mivolo:Multi-inputtransformerforageandgenderestimation,in:AnalysisofImages,SocialNetworks and Texts, Springer Nature Switzerland, Cham.

Bridging the gap in FER: addressing age bias in deep learning Mivolo:Multi-inputtransformerforageandgenderestimation,in:AnalysisofImages,SocialNetworks and Texts, Springer Nature Switzerland, Cham

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This paper cites Presentation and validation of the radboud faces database.

Bridging the gap in FER: addressing age bias in deep learning Presentation and validation of the radboud faces database

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Bridging the gap in FER: addressing age bias in deep learning Deep facial expression recognition: A survey

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This paper cites Exploring disentangled feature representation beyond face identification, in: 2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition, pp.

Bridging the gap in FER: addressing age bias in deep learning Exploring disentangled feature representation beyond face identification, in: 2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition, pp

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This paper cites Swin Transformer: Hierarchical Vision Transformer using Shifted Windows.

Bridging the gap in FER: addressing age bias in deep learning Swin Transformer: Hierarchical Vision Transformer using Shifted Windows

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This paper cites A ConvNet for the 2020s.

Bridging the gap in FER: addressing age bias in deep learning A ConvNet for the 2020s

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This paper cites Analysisofgenderdifferencesinfacialexpressionrecognitionbasedondeeplearningusing explainable artificial intelligence.

Bridging the gap in FER: addressing age bias in deep learning Analysisofgenderdifferencesinfacialexpressionrecognitionbasedondeeplearningusing explainable artificial intelligence

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Bridging the gap in FER: addressing age bias in deep learning A survey on bias and fairness in machine learning

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Bridging the gap in FER: addressing age bias in deep learning Thecreationandvalidationofthedevelopmentalemotionalfacesstimulusset

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Bridging the gap in FER: addressing age bias in deep learning Alifespandatabaseofadultfacialstimuli

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Bridging the gap in FER: addressing age bias in deep learning Assessingfidelityinxaipost-hoctechniques:Acomparativestudywithgroundtruth explanations datasets

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This paper cites Affectnet: A database for facial expression, valence, and arousal computing in the wild.

Bridging the gap in FER: addressing age bias in deep learning Affectnet: A database for facial expression, valence, and arousal computing in the wild

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This paper cites Facial expression recognition software | FaceReader.

Bridging the gap in FER: addressing age bias in deep learning Facial expression recognition software | FaceReader

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Bridging the gap in FER: addressing age bias in deep learning Warsawsetofemotionalfacialexpression pictures: A validation study of facial display photographs

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This paper cites Facial emotion recognition analysis based on age-biased data.

Bridging the gap in FER: addressing age bias in deep learning Facial emotion recognition analysis based on age-biased data

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This paper cites Shape preserving facial landmarks with graph attention networks, in: 33rd British Machine Vision Conference 2022, BMVC 2022, London, UK, November 21-24, 2022, BMVA Press.

Bridging the gap in FER: addressing age bias in deep learning Shape preserving facial landmarks with graph attention networks, in: 33rd British Machine Vision Conference 2022, BMVC 2022, London, UK, November 21-24, 2022, BMVA Press

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Bridging the gap in FER: addressing age bias in deep learning A novel approach to cross dataset studies in facial expression recognition

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This paper cites Explainablefacialexpressionrecognitionforpeoplewith intellectual disabilities, in: Proceedings of the XXIII International Conference on Human Computer Interaction.

Bridging the gap in FER: addressing age bias in deep learning Explainablefacialexpressionrecognitionforpeoplewith intellectual disabilities, in: Proceedings of the XXIII International Conference on Human Computer Interaction

Reference 54

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This paper cites Whyshoulditrustyou?:Explainingthepredictionsofanyclassifier,in:Proceedingsofthe22nd ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, p.

Bridging the gap in FER: addressing age bias in deep learning Whyshoulditrustyou?:Explainingthepredictionsofanyclassifier,in:Proceedingsofthe22nd ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, p

Reference 55

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Bridging the gap in FER: addressing age bias in deep learning A meta-analytic review of emotion recognition and aging: Implications for neuropsychological models of aging

Reference 57

Resolution: verified exact; doi, observed 2026-08-06T18:42:48.177337Z

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Bridging the gap in FER: addressing age bias in deep learning Density-based weighting for imbalanced regression

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Reference 60

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Bridging the gap in FER: addressing age bias in deep learning A computational study on aging effect for facial expression recognition

Reference 61

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This paper cites Enhancedfacialexpressionrecognitionbyage,in:201511thIEEEInternationalConferenceandWorkshops on Automatic Face and Gesture Recognition (FG), pp.

Bridging the gap in FER: addressing age bias in deep learning Enhancedfacialexpressionrecognitionbyage,in:201511thIEEEInternationalConferenceandWorkshops on Automatic Face and Gesture Recognition (FG), pp

Reference 62

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This paper cites Investigating bias and fairness in facial expression recognition, in: Computer Vision – ECCV 2020 Workshops, Springer International Publishing, Cham.

Bridging the gap in FER: addressing age bias in deep learning Investigating bias and fairness in facial expression recognition, in: Computer Vision – ECCV 2020 Workshops, Springer International Publishing, Cham

Reference 63

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This paper cites Joint estimation of age and expression by combining scattering and convolutional networks.

Bridging the gap in FER: addressing age bias in deep learning Joint estimation of age and expression by combining scattering and convolutional networks

Reference 64

Resolution: verified exact; doi, observed 2026-08-06T18:42:47.724689Z

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Bridging the gap in FER: addressing age bias in deep learning Ageprogression/regressionbyconditionaladversarialautoencoder,in:2017IEEEConferenceonComputer Vision and Pattern Recognition (CVPR), pp

Reference 65

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Bridging the gap in FER: addressing age bias in deep learning Defining standard values for facereader facial expression software output

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