Cited by 6,019Emotion and Mood RecognitionFace recognition and analysisFace Recognition and Perception

The DOI matches its Crossref record, with a small difference in title or year.

Facial Action Coding System

Ekman, Paul, Friesen, Wallace V.·2019·PsycTESTS Dataset

DOI 10.1037/t27734-000

Open this paper in CoChat — free account

Integrity signals

Registry

Crossref · 10.1037/t27734-000

Cites

Statistics

Recomputing p-values needs the paper’s full text.

Claims the paper makes

We couldn’t retrieve this paper’s full text, so its claims and self-check weren’t run. The registry and citation checks still apply.

Claims other papers make about this one

Each is checked against this paper’s own text: does it say what the citing paper says it does?

Still being checked.

Sorted by citations

Items 501–600 of 1,027

Emotion recognition from geometric facial features using self-organizing map
Majumder, A., Behera, L., & Subramanian, V. K. (2013) · Pattern Recognition · doi:10.1016/j.patcog.2013.10.010 · Cited by 134
Objective Classes for Micro-Facial Expression Recognition
Davison, A. K., Merghani, W., & Yap, M. H. (2018) · Journal of Imaging · doi:10.3390/jimaging4100119 · Cited by 134
Efficientnet-Lite and Hybrid CNN-KNN Implementation for Facial Expression Recognition on Raspberry Pi
Wahab, M. N. A., Nazir, A., Ren, A. T. Z., Noor, M. H. M., Akbar, M. F., & Mohamed, A. S. A. (2021) · IEEE Access · doi:10.1109/access.2021.3113337 · Cited by 134
A Proposal for Multimodal Emotion Recognition Using Aural Transformers and Action Units on RAVDESS Dataset
Luna-Jiménez, C., Kleinlein, R., Griol, D., Callejas, Z., Montero, J. M., & Fernández-Martínez, F. (2021) · Applied Sciences · doi:10.3390/app12010327 · Cited by 134
Building Expression into Virtual Characters
Vinayagamoorthy, V., Gillies, M. F. P., Steed, A. J., Tanguy, E., Pan, X., Loscos, C., & Slater, M. (2006) · Goldsmiths Research Online · doi:10.2312/egst.20061052 · Cited by 134
Cultural context moderates the relationship between emotion control values and cardiovascular challenge versus threat responses
Mauss, I. B., & Butler, E. A. (2009) · Biological Psychology · doi:10.1016/j.biopsycho.2009.09.010 · Cited by 133
The mathematics of marital conflict: Dynamic mathematical nonlinear modeling of newlywed marital interaction.
Gottman, J. M., Swanson, C., & Murray, J. (1999) · Journal of Family Psychology · doi:10.1037/0893-3200.13.1.3 · Cited by 133
ViTFER: Facial Emotion Recognition with Vision Transformers
Chaudhari, A., Bhatt, C., Krishna, A., & Mazzeo, P. L. (2022) · Applied System Innovation · doi:10.3390/asi5040080 · Cited by 133
Evidence for strong dissociation between emotion and facial displays: The case of surprise.
Reisenzein, R., Bördgen, S., Holtbernd, T., & Matz, D. (2006) · Journal of Personality and Social Psychology · doi:10.1037/0022-3514.91.2.295 · Cited by 133
The Digital Emily project
Alexander, O., Mike Rogers, A., Lambeth, W., Chiang, M. J., & Debevec, P. E. (2009) · ACM SIGGRAPH Courses · doi:10.1145/1667239.1667251 · Cited by 133
The facial displays of leaders: Toward an ethology of human politics
Masters, R. D., SULLIVAN, D., Lanzetta, J. T., McHugo, G. J., & Englis, B. G. (1986) · Journal of Social and Biological Systems · doi:10.1016/s0140-1750(86)90190-9 · Cited by 133
Dementia and response to pain in the elderly
Porter, F. L., Malhotra, K. M., Wolf, C. M., Morris, J. C., Miller, J. P., & Smith, M. C. (1996) · Pain · doi:10.1016/s0304-3959(96)03210-1 · Cited by 133
A Systematic Literature Review of Emotion Regulation Measurement in Individuals With Autism Spectrum Disorder
Weiss, J. A., Thomson, K., & Chan, L. (2014) · Autism Research · doi:10.1002/aur.1426 · Cited by 132
Social Psychophysiology for Social and Personality Psychology
Blascovich, J., Vanman, E. J., Mendes, W. B., & Dickerson, S. S. (2011) · SAGE Publications Ltd eBooks · doi:10.4135/9781446287842 · Cited by 132
State and Trait Cheerfulness and the Induction of Exhilaration
Ruch, W. (1997) · European Psychologist · doi:10.1027/1016-9040.2.4.328 · Cited by 132
What's in a smile?
Messinger, D. S., Fogel, A., & Dickson, K. L. (1999) · Developmental Psychology · doi:10.1037//0012-1649.35.3.701 · Cited by 132
Automatic apex frame spotting in micro-expression database
Liong, S., See, J., Wong, K., Ngo, A. C. L., Oh, Y.-H., & Phan, R. C. ‐. (2015) · Asian Conference on Pattern Recognition · doi:10.1109/acpr.2015.7486586 · Cited by 132
Automatic Facial Expression Recognition Using DCNN
Mayya, V., Pai, R. M., & Pai, M. M. M. (2016) · Procedia Computer Science · doi:10.1016/j.procs.2016.07.233 · Cited by 132
Computational Models of Emotion Inference in Theory of Mind: A Review and Roadmap
Ong, D. C., Zaki, J., & Goodman, N. D. (2018) · Topics in Cognitive Science · doi:10.1111/tops.12371 · Cited by 132
Attachment-Related Differences in Emotion Regulation in Adults: A Systematic Review on Attachment Representations
Eilert, D. W., & Buchheim, A. (2023) · Brain Sciences · doi:10.3390/brainsci13060884 · Cited by 131
Efficient Region-Aware Neural Radiance Fields for High-Fidelity Talking Portrait Synthesis
Li, J., Zhang, J., Bai, X. P., Zhou, J. W., & Gu, L. (2023) · IEEE/CVF International Conference on Computer Vision (ICCV) · doi:10.1109/iccv51070.2023.00696 · Cited by 131
Pain expression in patients with shoulder pathology: validity, properties and relationship to sickness impact
Prkachin, K. M., & Mercer, S. R. (1989) · Pain · doi:10.1016/0304-3959(89)90038-9 · Cited by 131
Thriving With Social Purpose: An Integrative Approach to the Development of Optimal Human Functioning
Ford, M. E., & Smith, P. R. (2007) · Educational Psychologist · doi:10.1080/00461520701416280 · Cited by 130
Bayesian Tensor Approach for 3-D Face Modeling
Tao, D., Song, M., Li, X., Shen, J., Sun, J., Wu, X., Faloutsos, C., & Maybank, S. J. (2008) · IEEE Transactions on Circuits and Systems for Video Technology · doi:10.1109/tcsvt.2008.2002825 · Cited by 130
Analysis and synthesis of facial image sequences in model-based image coding
Choi, C. S., Aizawa, K., Harashima, H., & Takebe, T. (1994) · IEEE Transactions on Circuits and Systems for Video Technology · doi:10.1109/76.305871 · Cited by 130
Developments in model-based video coding
Pearson, D. E. (1995) · Proceedings of the IEEE · doi:10.1109/5.387091 · Cited by 130
A Vision System for Observing and Extracting Facial Action Parameters
Essa, I. A., & Pentland, A. (1994) · Cited by 130
Regression-based intensity estimation of facial action units
Savran, A., Sankur, B., & Taha Bilge, M. (2012) · Image and Vision Computing · doi:10.1016/j.imavis.2011.11.008 · Cited by 129
FERA 2017 - Addressing Head Pose in the Third Facial Expression Recognition and Analysis Challenge
Valstar, M., Sánchez, E., Cohn, J. F., Jeni, L. A., Girard, J. M., Zhang, Z., Yin, L., & Pantić, M. (2017) · International Conference on Automatic Face and Gesture Recognition · doi:10.1109/fg.2017.107 · Cited by 129
Emotion Analysis in Man-Machine Interaction Systems
Balomenos, T., Raouzaiou, A. T., Ioannou, S. V., Drosopoulos, A., Karpouzis, K. C., & Kollias, S. (2005) · Lecture notes in computer science · doi:10.1007/978-3-540-30568-2_27 · Cited by 129
Facial expressions of emotion and psychopathology in adolescent boys.
Keltner, D. J., Moffitt, T. E., & Stouthamer‐Loeber, M. (1995) · Journal of Abnormal Psychology · doi:10.1037//0021-843x.104.4.644 · Cited by 129
Randomised controlled trial of paracetamol for heel prick pain in neonates
Shah, V. S., Taddio, A., & Ohlsson, A. (1998) · Archives of Disease in Childhood Fetal & Neonatal · doi:10.1136/fn.79.3.f209 · Cited by 129
AVEC 2016 - Depression, Mood, and Emotion Recognition Workshop and ChallengePreprint
Valstar, M., Gratch, J. S., Schuller, B. W., Ringeval, F., Lalanne, D., Torres, M. T., Scherer, S. J., Stratou, G., Cowie, R., & Pantić, M. (2016) · arXiv (Cornell University) · doi:10.48550/arxiv.1605.01600 · Cited by 129
Is the Putative Mirror Neuron System Associated with Empathy? A Systematic Review and Meta-Analysis
Bekkali, S., Youssef, G. J., Donaldson, P. H., Albein-Urios, N., Hyde, C., & Enticott, P. G. (2021) · Neuropsychology Review · doi:10.1007/s11065-020-09452-6 · Cited by 128
Neural Head Reenactment with Latent Pose Descriptors
Burkov, E., Pasechnik, I., Grigorev, A., & Lempitsky, V. (2020) · IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings - IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings · doi:10.1109/cvpr42600.2020.01380 · Cited by 128
A Survey of Autonomous Human Affect Detection Methods for Social Robots Engaged in Natural HRI
McColl, D., Hong, A., Hatakeyama, N., Nejat, G., & Benhabib, B. (2015) · Journal of Intelligent & Robotic Systems · doi:10.1007/s10846-015-0259-2 · Cited by 127
Crowdsourcing Facial Responses to Online Videos
McDuff, D., el Kaliouby, R., & Picard, R. W. (2012) · IEEE Transactions on Affective Computing · doi:10.1109/t-affc.2012.19 · Cited by 127
Features versus Context: An Approach for Precise and Detailed Detection and Delineation of Faces and Facial Features
Ding, L., & Martínez, A. M. (2010) · IEEE Transactions on Pattern Analysis and Machine Intelligence · doi:10.1109/tpami.2010.28 · Cited by 127
Development and application of emotion recognition technology — a systematic literature review
Guo, R., Guo, H., Wang, L., Chen, M., Dong, Y., & Li, B. (2024) · BMC Psychology · doi:10.1186/s40359-024-01581-4 · Cited by 127
Encoding and decoding of pain expressions: a judgement study
Prkachin, K. M., Berzins, S. A., & Mercer, S. R. (1994) · Pain · doi:10.1016/0304-3959(94)90206-2 · Cited by 127
Selection for universal facial emotion.
Waller, B. M., Cray, J. J., & Burrows, A. M. (2008) · Emotion · doi:10.1037/1528-3542.8.3.435 · Cited by 126
Interactive region-based linear 3D face models
Tena, J. R., la Torre, F. D., & Matthews, I. (2011) · ACM SIGGRAPH Conference (SIGGRAPH) · doi:10.1145/1964921.1964971 · Cited by 126
The effects of alcohol on cigarette craving in heavy smokers and tobacco chippers.
Sayette, M. A., Martin, C. S., Wertz, J. M., Perrott, M. A., & Peters, A. (2005) · Psychology of Addictive Behaviors · doi:10.1037/0893-164x.19.3.263 · Cited by 126
A survey: facial micro-expression recognition
Takalkar, M. A., Xu, M. G., Wu, Q., & Chaczko, Z. (2017) · Multimedia Tools and Applications · doi:10.1007/s11042-017-5317-2 · Cited by 126
Emotion recognition for enhanced learning: using AI to detect students’ emotions and adjust teaching methods
Salloum, S. A., Alomari, K. M., Alfaisal, A. M., Aljanada, R. A., & Basiouni, A. (2025) · Smart Learning Environments · doi:10.1186/s40561-025-00374-5 · Cited by 126
Facial Expression Recognition Based on 3D Dynamic Range Model Sequences
Sun, Y., & Yin, L. (2008) · Lecture notes in computer science · doi:10.1007/978-3-540-88688-4_5 · Cited by 125
Pain and negative emotions in the face: judgements by health care professionals
Kappesser, J., & Williams, A. C. D. C. (2002) · Pain · doi:10.1016/s0304-3959(02)00101-x · Cited by 125
Neuropsychological Studies of Linguistic and Affective Facial Expressions in Deaf Signers
Corina, D. P., Bellugi, U., & Reilly, J. S. (1999) · Language and Speech · doi:10.1177/00238309990420020801 · Cited by 125
CAS(ME)3: A Third Generation Facial Spontaneous Micro-Expression Database with Depth Information and High Ecological Validity
Li, J., Dong, Z., Lu, S., Wang, S., Yan, W., Ma, Y., Liu, Y., Huang, C., & Fu, X. (2022) · IEEE Transactions on Pattern Analysis and Machine Intelligence · doi:10.1109/tpami.2022.3174895 · Cited by 125
Semi-Structural Interview-Based Chinese Multimodal Depression Corpus Towards Automatic Preliminary Screening of Depressive Disorders
Zou, B., Han, J., Wang, Y., Liu, R., Zhao, S., Feng, L., Lyu, X., & Ma, H. (2022) · IEEE Transactions on Affective Computing · doi:10.1109/taffc.2022.3181210 · Cited by 125
Comparing the Ideation Quality of Humans With Generative Artificial Intelligence
Joosten, J., Bilgram, V., Hahn, A., & Totzek, D. (2024) · IEEE Engineering Management Review · doi:10.1109/emr.2024.3353338 · Cited by 125
Marital Sentiment Override: Does It Influence Couples' Perceptions?
Hawkins, M., Carrère, S., & Gottman, J. M. (2002) · Journal of Marriage and the Family · doi:10.1111/j.1741-3737.2002.00193.x · Cited by 125
Capturing emotion reactivity through physiology measurement as a foundation for affective engineering in engineering design science and engineering practices
Balters, S., & Steinert, M. (2015) · Journal of Intelligent Manufacturing · doi:10.1007/s10845-015-1145-2 · Cited by 124
Recognizing Threat: A Simple Geometric Shape Activates Neural Circuitry for Threat Detection
Larson, C. L., Aronoff, J., Sarinopoulos, I. C., & Zhu, D. C. (2008) · Journal of Cognitive Neuroscience · doi:10.1162/jocn.2009.21111 · Cited by 124
Smile and the world will smile with you—The effects of a virtual agent‘s smile on users’ evaluation and behavior
Krämer, N. C., Kopp, S., Becker-Asano, C., & Sommer, N. (2012) · International Journal of Human-Computer Studies · doi:10.1016/j.ijhcs.2012.09.006 · Cited by 124
A Model Based Method for Automatic Facial Expression Recognition
van Kuilenburg, H., Wiering, M., & den Uyl, M. J. (2005) · Lecture notes in computer science · doi:10.1007/11564096_22 · Cited by 124
The nuts and bolts of behavioral observation of marital and family interaction
Margolin, G., Oliver, P. H., Gordis, E. B., O'Hearn, H. G., Medina, A. M., Ghosh, C. M., & Morland, L. (1998) · Clinical Child and Family Psychology Review · doi:10.1023/a:1022608117322 · Cited by 123
Measuring changes in emotion during psychotherapy: Conceptual and methodological issues.
Sloan, D. M., & Kring, A. M. (2007) · Clinical Psychology Science and Practice · doi:10.1111/j.1468-2850.2007.00092.x · Cited by 123
Intelligent facial emotion recognition and semantic-based topic detection for a humanoid robot
Zhang, L., Jiang, M. X., Farid, D. M., & Hossain, M. A. (2013) · Expert Systems with Applications · doi:10.1016/j.eswa.2013.03.016 · Cited by 123
Vision-based patient monitoring: a comprehensive review of algorithms and technologies
Sathyanarayana, S., Satzoda, R. K., Sathyanarayana, S., & Srikanthan, T. (2015) · Journal of Ambient Intelligence and Humanized Computing · doi:10.1007/s12652-015-0328-1 · Cited by 123
RELATIONSHIPS AMONG AD-INDUCED AFFECT, BELIEFS, AND ATTITUDES: Another Look
Homer, P. M. (2006) · Journal of Advertising · doi:10.2753/joa0091-3367350103 · Cited by 123
Facial expression recognition from line-based caricatures
Gao, Y., Leung, M. K. H., Hui, S. C., & Tananda, M. W. (2003) · IEEE Transactions on Systems Man and Cybernetics - Part A Systems and Humans · doi:10.1109/tsmca.2003.817057 · Cited by 123
Facial expression recognition via deep learning
Lv, Y., Feng, Z., & Xu, C. (2014) · 2014 International Conference on Smart Computing · doi:10.1109/smartcomp.2014.7043872 · Cited by 122
The relationship between smile type and play type during parent–infant play
Dickson, K. L., Walker, H., & Fogel, A. (1997) · Developmental Psychology · doi:10.1037/0012-1649.33.6.925 · Cited by 122
I show you how I like you - can you read it in my face? [robotics]
Cañamero, L. D., & Fredslund, J. (2001) · IEEE Transactions on Systems Man and Cybernetics - Part A Systems and Humans · doi:10.1109/3468.952719 · Cited by 122
Differentiation of personal distress and sympathy in children and adults.
Eisenberg, N., Schaller, M., Fabes, R. A., Bustamante, D., Mathy, R. M., Shell, R. M., & Rhodes, K. (1988) · Developmental Psychology · doi:10.1037/0012-1649.24.6.766 · Cited by 122
Social-Cognitive Remediation in Schizophrenia: Generalization of Effects of the Training of Affect Recognition (TAR)
Wölwer, W., & Frommann, N. (2011) · Schizophrenia Bulletin · doi:10.1093/schbul/sbr071 · Cited by 122
Criteria for Emotion Recognition from Verbal and Nonverbal Expression: Studying Baggage Loss in the Airport
Scherer, K. R., & Ceschi, G. (2000) · Personality and Social Psychology Bulletin · doi:10.1177/0146167200265006 · Cited by 122
First Impressions in Human--Agent Virtual Encounters
Cafaro, A., Vilhjálmsson, H. H., & Bickmore, T. (2016) · ACM Transactions on Computer-Human Interaction · doi:10.1145/2940325 · Cited by 120
Emotions in Problem Solving
Hannula, M. S. (2015) · Springer eBooks · doi:10.1007/978-3-319-17187-6_16 · Cited by 120
Distinct facial expressions represent pain and pleasure across cultures
Chen, C., Crivelli, C., Garrod, O., Schyns, P. G., Dols, J. M. F., & Jack, R. E. (2018) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1807862115 · Cited by 120
Facial expressivity in the course of schizophrenia and depression
Gäebel, W., & W�lwer, W. (2004) · European Archives of Psychiatry and Clinical Neuroscience · doi:10.1007/s00406-004-0510-5 · Cited by 120
Interpersonal resources in action
(2001) · Semiotica · doi:10.1515/semi.2001.056 · Cited by 120
Mechanisms of Alcohol-Facilitated Intimate Partner Violence
Eckhardt, C. I., Parrott, D. J., & Sprunger, J. G. (2015) · Violence Against Women · doi:10.1177/1077801215589376 · Cited by 119
Dynamic Micro-Expression Recognition Using Knowledge Distillation
Sun, B., Cao, S., Li, D., He, J. Y. D., & Yu, L. (2020) · IEEE Transactions on Affective Computing · doi:10.1109/taffc.2020.2986962 · Cited by 119
A Spontaneous Driver Emotion Facial Expression (DEFE) Dataset for Intelligent Vehicles: Emotions Triggered by Video-Audio Clips in Driving Scenarios
Li, W., Cui, Y., Ma, Y., Chen, X., Li, G., Zeng, G., Guo, G., & Cao, D. (2021) · IEEE Transactions on Affective Computing · doi:10.1109/taffc.2021.3063387 · Cited by 119
The Intentionality Model and Language Acquisition: Engagement, Effort, and the Essential Tension in Development
Bloom, L. M., Tinker, E., & Scholnick, E. K. (2001) · PubMed · doi:10.7916/d8x92br8 · Cited by 119
Dynamic 3-D scene analysis through synthesis feedback control
Koch, R. (1993) · IEEE Transactions on Pattern Analysis and Machine Intelligence · doi:10.1109/34.216725 · Cited by 119
Effects of Acute Tryptophan Depletion on Mood and Facial Emotion Perception Related Brain Activation and Performance in Healthy Women with and without a Family History of Depression
van der Veen, F. M., Evers, E. A. T., Deutz, N. E. P., & Schmitt, J. A. J. (2007) · Neuropsychopharmacology · doi:10.1038/sj.npp.1301212 · Cited by 118
Human-Centred Intelligent Human Computer Interaction (HCI²): how far are we from attaining it?
Pantić, M., Nijholt, A., Pentland, A., & Huanag, T. S. (2008) · International Journal of Autonomous and Adaptive Communications Systems · doi:10.1504/ijaacs.2008.019799 · Cited by 118
Duchenne smiles and the perception of generosity and sociability in faces
Méhu, M., Little, A. C., & Dunbar, R. (2007) · Journal of Evolutionary Psychology · doi:10.1556/jep.2007.1011 · Cited by 118
Comparison of Deliberate and Spontaneous Facial Movement in Smiles and Eyebrow Raises
Schmidt, K. L., Bhattacharya, S., & Denlinger, R. (2009) · Journal of Nonverbal Behavior · doi:10.1007/s10919-008-0058-6 · Cited by 117
A Multimodal Emotion Detection System during Human–Robot Interaction
Alonso-Martín, F., Malfáz, M., Sequeira, J. S., Gorostiza, J. F., & Salichs, M. A. (2013) · Sensors · doi:10.3390/s131115549 · Cited by 117
Functional and Structural Deficits in Brain Regions Subserving Face Perception in Schizophrenia
Onitsuka, T., Niznikiewicz, M. A., Spencer, K., Frumin, M., Kuroki, N., Lucia, L. C., Shenton, M. E., & McCarley, R. W. (2006) · American Journal of Psychiatry · doi:10.1176/appi.ajp.163.3.455 · Cited by 117
A Combination of Vocal f 0 Dynamic and Summary Features Discriminates between Three Pragmatic Categories of Infant-Directed Speech
Katz, G. S., Cohn, J. F., & Moore, C. A. (1996) · Child Development · doi:10.1111/j.1467-8624.1996.tb01729.x · Cited by 117
Individual differences in facial expression: stability over time, relation to self-reported emotion, and ability to inform person identification
Cohn, J. F., Schmidt, K. L., Ralph Gross, A., & Ekman, P. (2003) · INTERNATIONAL CONFERENCE ON MULTIMODAL INTERACTION · doi:10.1109/icmi.2002.1167045 · Cited by 117
Self-citation
The Asymmetry of Facial Actions is Inconsistent with Models of Hemispheric Specialization
Hager, J. C., & Ekman, P. (1985) · Psychophysiology · doi:10.1111/j.1469-8986.1985.tb01605.x · Cited by 117
Self-citation
Image coding-from waveforms in animation
Forchheimer, R., & Kronander, T. (1989) · IEEE Transactions on Acoustics Speech and Signal Processing · doi:10.1109/29.45550 · Cited by 117
Needs and challenges in human computer interaction for processing social emotional information
Esposito, A. A., Esposito, A. M., & Vogel, C. M. (2015) · Pattern Recognition Letters · doi:10.1016/j.patrec.2015.02.013 · Cited by 116
Facial expressions as honest signals of cooperative intent in a one-shot anonymous Prisoner's Dilemma game
Reed, L. I., Zeglen, K. N., & Schmidt, K. L. (2011) · Evolution and Human Behavior · doi:10.1016/j.evolhumbehav.2011.09.003 · Cited by 116
Control of facial expressions of the humanoid robot head ROMAN
Berns, K., & Hirth, J. (2006) · IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS) · doi:10.1109/iros.2006.282331 · Cited by 116
Bodily Communication of Emotion: Evidence for Extrafacial Behavioral Expressions and Available Coding Systems
Witkower, Z., & Tracy, J. L. (2018) · Emotion Review · doi:10.1177/1754073917749880 · Cited by 116
Psychology Meets Machine Learning: Interdisciplinary Perspectives on Algorithmic Job Candidate Screening
Liem, C. C. S., Langer, M., Demetriou, A. M., Hiemstra, A. M. F., Wicaksana, A. S., Born, M. P., & König, C. J. (2018) · The Springer series on challenges in machine learning · doi:10.1007/978-3-319-98131-4_9 · Cited by 116
Recognition of Six basic facial expression and their strength by neural network
Kobayashi, H., & Hara, F. (2003) · IEEE RO-MAN · doi:10.1109/roman.1992.253857 · Cited by 116
Darwin's Legacy and the Study of Primate Visual Communication
De WAAL, F. B. M. (2003) · Annals of the New York Academy of Sciences · doi:10.1196/annals.1280.003 · Cited by 115
The r FaceReader: Online facial expression recognition.
y l, D. U. (2005) · Cited by 115
Behavioral and Physiological Signals-Based Deep Multimodal Approach for Mobile Emotion Recognition
Yang, K., Wang, C., Gu, Y., Sarsenbayeva, Z., Tag, B., Dingler, T., Wadley, G., & Gonçalves, J. (2021) · IEEE Transactions on Affective Computing · doi:10.1109/taffc.2021.3100868 · Cited by 115
Recognition of Emotions in Gait Patterns by Means of Artificial Neural Nets
Janssen, D., Schöllhorn, W. I., Lubienetzki, J., Fölling, K., Kokenge, H., & Davids, K. (2008) · Journal of Nonverbal Behavior · doi:10.1007/s10919-007-0045-3 · Cited by 115
The dynamic still-face effect: Do infants decrease bidding over time when parents are not responsive?
Ekas, N. V., Haltigan, J. D., & Messinger, D. S. (2012) · Developmental Psychology · doi:10.1037/a0029330 · Cited by 114
Phace
Ichim, A.-E., Kadleček, P., Kavan, L., & Pauly, M. V. (2017) · ACM Transactions on Graphics · doi:10.1145/3072959.3073664 · Cited by 114

Authors: Ekman, P., & Friesen, W. V.
Venue: PsycTESTS Dataset
Publisher: American Psychological Association (APA)
Published: 1978
DOI: 10.1037/t27734-000
OpenAlex: W1588539311
Cited by: 6,019
References: 0
Citations by year: 2026: 288 · 2025: 447 · 2024: 367 · 2023: 379 · 2022: 314 · 2021: 204 · 2020: 218 · 2019: 195 · 2018: 227 · 2017: 199 · 2016: 244 · 2015: 233 · 2014: 214 · 2013: 208 · 2012: 174
Type: dataset
Language: en
Open access: closed
Locations: PsycTESTS Dataset (publishedVersion)
Topics: Physical Sciences › Computer Science › Artificial Intelligence › Emotion and Mood Recognition
Physical Sciences › Computer Science › Computer Vision and Pattern Recognition › Face recognition and analysis
Life Sciences › Neuroscience › Cognitive Neuroscience › Face Recognition and Perception
Keywords: facial expressions, facial action units, emotion recognition, facial motion

About these checks

Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

Statistics and arithmetic are recomputed, not judged.

Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.

What counts as a claim ›How we measure confidence ›How we check this ›

Are you an author, or do you see a problem with this page? Request a review

Facial Action Coding System

Overview

Integrity signals

Verification

Claims the paper makes

Claims other papers make about this one

Citations

Cites

Cited by

Related

Metadata

Record

About these checks