The DOI matches its Crossref record; 26 of the 26 references it cites were found in a registry or an index.
The Karolinska Directed Emotional Faces: A validation study
Abstract
Although affective facial pictures are widely used in emotion research, standardised affective stimuli sets are rather scarce, and the existing sets have several limitations. We therefore conducted a validation study of 490 pictures of human facial expressions from the Karolinska Directed Emotional Faces database (KDEF). Pictures were evaluated on emotional content and were rated on an intensity and arousal scale. Results indicate that the database contains a valid set of affective facial pictures. Hit rates, intensity, and arousal of the 20 best KDEF pictures for each basic emotion are provided in an appendix.
Overview
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
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?
In the citing paper
“This validated stimulus set [47] has been used in numerous social cognitive reaction time studies [48], [5], [49]”
From A direct examination of the effect of intranasal administration of oxytocin on approach-avoidance motor responses to emotional stimuli (2013) · cites this paper as [47]
Citations
Cites
Ekman, P., & Friesen, W. V. (2019) · PsycTESTS Dataset · doi:10.1037/t27734-000 · Cited by 6,019
(2001) · doi:10.1017/cbo9780511546396 · Cited by 4,482
Ekman, P. (1976) · Medical Entomology and Zoology · Cited by 4,345
Ekman, P. (1993) · American Psychologist · doi:10.1037/0003-066x.48.4.384 · Cited by 3,441
Looking at pictures: Affective, facial, visceral, and behavioral reactions
LANG, P. J., GREENWALD, M. K., BRADLEY, M. M., & HAMM, A. O. (1993) · Psychophysiology · doi:10.1111/j.1469-8986.1993.tb03352.x · Cited by 3,190
International Affective Picture System (IAPS) : Technical Manual and Affective Ratings
Lang, P. J. (1995) · Medical Entomology and Zoology · Cited by 2,870
Emotion elicitation using films
Gross, J. J., & Levenson, R. W. (1995) · Cognition & Emotion · doi:10.1080/02699939508408966 · Cited by 2,179
Likableness ratings of 555 personality-trait words.
Anderson, N. H. (1968) · Journal of Personality and Social Psychology · doi:10.1037/h0025907 · Cited by 1,670
Motivated attention : affect, activation, and action
Lang, P. J., Bradley, M. M., & Cuthbert, B. N. (1997) · Medical Entomology and Zoology · Cited by 1,486
Do threatening stimuli draw or hold visual attention in subclinical anxiety?
Fox, E., Russo, R., Bowles, R., & Dutton, K. (2001) · Journal of Experimental Psychology: General · doi:10.1037/0096-3445.130.4.681 · Cited by 1,469
Research works printed but not linked: 7
- Beaupré M. G., 2000, The Montreal Set of Facial Displays of Emotion
- Bradley M. M., 1999, Affective Norms for English Words (ANEW): Instruction manual and affective ratings. Technical report no. B-2
- Bradley M. M., 1999, International Affective Digitized Sounds (IADS): Stimuli, instruction manual and affective ratings. Technical report no. B-2
- Lundqvist D., 1998, The Karolinska Directed Emotional Faces (KDEF)
- Matsumoto D., 1988, Japanese and Caucasian facial expressions of emotion (JACFEE)
- Messina D., 1989, Cahiers de Psychologie Cognitive, 9, 165
- Schaefer A., 2005, A multi-criteria assessment of emotional films
Cited by
Sorted by citations
Items 401–500 of 790
Multi-Dimensional, Nuanced and Subjective – Measuring the Perception of Facial Expressions
Bryant, D. G., Deng, S., Sephus, N. H., Xia, W., & Perona, P. (2022) · 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/cvpr52688.2022.02026 · Cited by 11
Attentional Bias Among High and Low Ruminators: Eye Tracking Study in a Non-Clinical Population
Arënliu, A., Konjufca, J., Meiran, N., Weine, S. M., & Langenecker, S. A. (2023) · SAGE Open · doi:10.1177/21582440231170804 · Cited by 10
Hierarchical status is rapidly assessed from behaviourally dominant faces
Pegna, A. J., Framorando, D., Yu, Z., Buhmann, Z., Nelson, N. L., & Dixson, B. J. W. (2023) · Cognitive Affective & Behavioral Neuroscience · doi:10.3758/s13415-023-01108-1 · Cited by 10
Emotional faces influence evaluation of natural and transformed food
Manippa, V., Padulo, C., & Brancucci, A. (2017) · Psychological Research · doi:10.1007/s00426-017-0857-7 · Cited by 10
Angry faces are tracked more easily than neutral faces during multiple identity tracking
Li, J., Oksama, L., Nummenmaa, L., & Hyönä, J. (2017) · Cognition & Emotion · doi:10.1080/02699931.2017.1315929 · Cited by 10
Amorim, M., & Pinheiro, A. P. (2018) · Cognition & Emotion · doi:10.1080/02699931.2018.1452718 · Cited by 10
2.5D Facial Personality Prediction Based on Deep Learning
Xu, J. D., Tian, W., Lv, G., Liu, S., & Fan, Y. (2021) · Journal of Advanced Transportation · doi:10.1155/2021/5581984 · Cited by 10
Frank, R., Schulze, L., Hellweg, R., Koehne, S., & Roepke, S. (2018) · Behaviour Research and Therapy · doi:10.1016/j.brat.2018.02.005 · Cited by 10
Development of the Youth Emotion Picture Set
Novello, B., Renner, A. M., Maurer, G., Musse, S. R., & Arteche, A. X. (2018) · Perception · doi:10.1177/0301006618797226 · Cited by 10
Emotional intelligence and emotional reactivity: Understanding the hypersensitivity hypothesis
Fiori, M., Gillioz, C., & Nicolet-dit-Félix, M. (2024) · Personality and Individual Differences · doi:10.1016/j.paid.2024.112792 · Cited by 9
Deep learning for emotion driven user experiences
Bisogni, C., Cascone, L., Castiglione, A., & Passero, I. (2021) · Pattern Recognition Letters · doi:10.1016/j.patrec.2021.09.004 · Cited by 9
Faces emotional expressions: from perceptive to motor areas in aged and young subjects
Loi, N., Ginatempo, F., Manca, A., Melis, F., & Deriu, F. (2021) · Journal of Neurophysiology · doi:10.1152/jn.00328.2021 · Cited by 9
Cavadini, T., Courbois, Y., & Gentaz, É. (2022) · PLoS ONE · doi:10.1371/journal.pone.0266176 · Cited by 13
Jointly Imputing Multi-View Data with Optimal Transport
Wu, Y., Miao, X., Huang, X., & Yin, J. (2023) · Proceedings of the AAAI Conference on Artificial Intelligence · doi:10.1609/aaai.v37i4.25599 · Cited by 9
The cross-race effect in automatic facial expression recognition violates measurement invariance
Li, Y., Yeh, S., & Huang, T.-R. (2023) · Frontiers in Psychology · doi:10.3389/fpsyg.2023.1201145 · Cited by 11
Long, D. T. (2024) · Cybernetics and Information Technologies · doi:10.2478/cait-2024-0010 · Cited by 9
Emotion Recognition beyond Pixels: Leveraging Facial Point Landmark Meshes
Arabian, H., Alshirbaji, T. A., Chase, J. G., & Möeller, K. (2024) · Applied Sciences · doi:10.3390/app14083358 · Cited by 9
Spatiotemporal Dynamics of Cortical Representations during and after Stimulus Presentation
van de Nieuwenhuijzen, M. E., van den Borne, E. W. P., Jensen, O. B., & van Gerven, M. A. J. (2016) · Frontiers in Systems Neuroscience · doi:10.3389/fnsys.2016.00042 · Cited by 9
Effects of Nodal Distance on Conditioned Stimulus Valences Across Time
Amd, M., Machado, A. D., de Oliveira, M. A., Passarelli, D. A., & de Rose, J. C. C. (2019) · Frontiers in Psychology · doi:10.3389/fpsyg.2019.00742 · Cited by 9
Assessment tools for social cognition in epilepsy
Bauer, J., Kegel, L., Steiger, B. K., & Jokeit, H. (2019) · Clinical Epileptology · doi:10.1007/s10309-019-0260-z · Cited by 11
Disentangling presentation and processing times in the brain
Caplette, L., Ince, R. A. A., Jerbi, K., & Gosselin, F. (2020) · NeuroImage · doi:10.1016/j.neuroimage.2020.116994 · Cited by 9
How expectations of pain elicited by consciously and unconsciously perceived cues unfold over time
Tu, Y., Pantazis, D., Wilson, G., Khan, S., Ahlfors, S. P., & Kong, J. (2021) · NeuroImage · doi:10.1016/j.neuroimage.2021.117985 · Cited by 9
PDSTD - The Portsmouth Dynamic Spontaneous Tears Database
Küster, D., Baker, M., & Krumhuber, E. G. (2021) · Behavior Research Methods · doi:10.3758/s13428-021-01752-w · Cited by 9
Impaired grouping of ambient facial images in autism
Gehdu, B. K., Gray, K. L. H., & Cook, R. (2022) · Scientific Reports · doi:10.1038/s41598-022-10630-0 · Cited by 9
Hartmann, T. J., Hartmann, J., Friebe-Hoffmann, U., Lato, C., Janni, W. J., & Látó, K. (2022) · Geburtshilfe und Frauenheilkunde · doi:10.1055/a-1866-2943 · Cited by 9
Depressive symptoms and cognitive control: the role of affective interference
Dell’Acqua, C., Benvenuti, S. M., Vallesi, A., Palomba, D., & Ambrosini, E. (2022) · Cognition & Emotion · doi:10.1080/02699931.2022.2128065 · Cited by 12
Young, M. E., & Brunet, P. M. (2011) · Journal of Individual Differences · doi:10.1027/1614-0001/a000036 · Cited by 9
Tinnitus, anxiety and automatic processing of affective information: an explorative study
Ooms, E., Vanheule, S., Meganck, R., Vinck, B., Watelet, J., & Dhooge, I. J. M. (2012) · European Archives of Oto-Rhino-Laryngology · doi:10.1007/s00405-012-2044-1 · Cited by 9
Development and validation of Indian Affective Picture Database
Sharma, U., & Bhushan, B. (2017) · International Journal of Psychology · doi:10.1002/ijop.12471 · Cited by 9
Jonassen, R., Foss Haug, K. B., Endestad, T., Bentsen, H., Grimholt, R. M., & Landrø, N. I. (2013) · Cognition & Emotion · doi:10.1080/02699931.2012.726213 · Cited by 8
Jardat, P., Menard--Peroy, Z., Parias, C., Reigner, F., Calandreau, L., & Lansade, L. (2024) · Behavioural Processes · doi:10.1016/j.beproc.2024.105081 · Cited by 8
Eicher, M., & Jokeit, H. (2022) · Acta Epileptologica · doi:10.1186/s42494-022-00093-1 · Cited by 9
Development and Validation of the AIIMS Facial Toolbox for Emotion Recognition
Verma, R., Kalsi, N., Shrivastava, N. P., & Sheerha, A. (2022) · Indian Journal of Psychological Medicine · doi:10.1177/02537176221111578 · Cited by 8
Faster social attention disengagement in individuals with higher autism traits
Goold, S., Murphy, M., Goodale, M. A., Crewther, S. G., & Laycock, R. (2022) · Journal of Clinical and Experimental Neuropsychology · doi:10.1080/13803395.2023.2167943 · Cited by 10
Pictorial Representations of Achievement Emotions: Preliminary Data with Children and Adults
Raccanello, D., & Bianchetti, C. (2014) · Advances in intelligent systems and computing · doi:10.1007/978-3-319-07698-0_16 · Cited by 8
'What is more familiar than I? Self, other and familiarity in schizophrenia
Ameller, A., Dereux, A., Dubertret, C., Vaïva, G., Thomas, P., & Pins, D. (2014) · Schizophrenia Research · doi:10.1016/j.schres.2014.12.007 · Cited by 8
Guntz, T., Balzarini, R., Vaufreydaz, D., & Crowley, J. L. (2018) · Multimodal Technologies and Interaction · doi:10.3390/mti2020011 · Cited by 8
Duchowski, A. T., Jörg, S., Screws, J., Gehrer, N. A., Schönenberg, M., & Krejtz, K. (2019) · ACM Symposium on Eye Tracking Research and Applications (ETRA) · doi:10.1145/3314111.3319848 · Cited by 8
Bill, G., Whyte, E. M., Griffin, J. W., & Scherf, K. S. (2020) · International Journal of Methods in Psychiatric Research · doi:10.1002/mpr.1833 · Cited by 8
The 4D Space-Time Dimensions of Facial Perception
Burt, A. L., & Crewther, D. P. (2020) · Frontiers in Psychology · doi:10.3389/fpsyg.2020.01842 · Cited by 13
Facial Emotion Perceptual Tendency in Violent and Non-violent Offenders
Zeng, Y., Liu, X., & Cheng, L. (2021) · Journal of Interpersonal Violence · doi:10.1177/0886260521989848 · Cited by 8
Morphset: Augmenting Categorical Emotion Datasets With Dimensional Affect Labels Using Face Morphing
Vonikakis, V., Neo, D., & WINKLER, S. S. (2021) · Proceedings - International Conference on Image Processing · doi:10.1109/icip42928.2021.9506566 · Cited by 8
Latent sparse transfer subspace learning for cross-corpus facial expression recognition
Zhang, W., Song, P., Chen, D., & Zhang, W. (2021) · Digital Signal Processing · doi:10.1016/j.dsp.2021.103121 · Cited by 8
Modified chess patterns: handcrafted feature descriptors for facial expression recognition
Kartheek, M. N., Prasad, M. V. N. K., & Bhukya, R. (2021) · Complex & Intelligent Systems · doi:10.1007/s40747-021-00526-3 · Cited by 8
Sun, Z., Zhang, H., Ma, S., & Hu, Z. (2022) · Artificial Intelligence Review · doi:10.1007/s10462-022-10160-1 · Cited by 8
Axelrod, V., Rozier, C., Malkinson, T. S., Lehongre, K., Adam, C., Lambrecq, V., Navarro, V., & Naccache, L. (2022) · Neuropsychologia · doi:10.1016/j.neuropsychologia.2022.108228 · Cited by 8
Schmidt, F., & Schmidt, T. (2013) · Visual Cognition · doi:10.1080/13506285.2013.793221 · Cited by 8
Investigating social-contextual determinants of cooperation in incarcerated violent offenders
Scheeff, J., Jusyte, A., & Schönenberg, M. (2018) · Scientific Reports · doi:10.1038/s41598-018-35450-z · Cited by 8
Updating the Chieti Affective Action Videos database with older adults
Malva, P. L., Ceccato, I., Crosta, A. D., Marín, A., Fasolo, M., Palumbo, R., Mammarella, N., Palumbo, R., & Domenico, A. D. (2021) · Scientific Data · doi:10.1038/s41597-021-01053-z · Cited by 8
Effective and Efficient Multi-View Imputation With Optimal Transport
Wu, Y., Miao, X., Nan, Z.-A., Zhang, J., Jian-hu, H., & Yin, J. (2024) · IEEE Transactions on Knowledge and Data Engineering · doi:10.1109/tkde.2024.3387439 · Cited by 7
The Italian Face-Name Association Test (ItFNAT): a preliminary validation of three parallel versions
Manippa, V., Caffò, A. O., & Rivolta, D. (2025) · Neurological Sciences · doi:10.1007/s10072-025-08165-z · Cited by 7
Kalhan, S., McFadyen, J., Tsuchiya, N., & Garrido, M. I. (2022) · Human Brain Mapping · doi:10.1002/hbm.25889 · Cited by 8
Kujala, J., Alexandrou, A. M., Lapinkero, H., Neely, A. S., Sipilä, S., & Parviainen, T. M. (2022) · Brain and Cognition · doi:10.1016/j.bandc.2022.105929 · Cited by 7
Santos, I. M., Bem‐Haja, P., Silva, A., Rosa, C., Queiroz, D. F., Alves, M. F., Barroso, T., Cerri, L., & da Silva, C. F. (2022) · Behavioral Sciences · doi:10.3390/bs13010038 · Cited by 9
Xiao, L., Baetens, K., & Deroost, N. (2024) · Cognition & Emotion · doi:10.1080/02699931.2023.2300751 · Cited by 9
Jiang, C.-S., Liu, Z., Fukushima, E. F., & She, J. (2025) · IEEE Transactions on Instrumentation and Measurement · doi:10.1109/tim.2025.3578178 · Cited by 8
Emotion Regulation in Intelligent Tutoring Systems: A Systematic Literature Review
Khadimallah, R., Abdelkefi, M., & Kallel, I. (2020) · IEEE International Conference on Teaching, Assessment, and Learning for Engineering · doi:10.1109/tale48869.2020.9368372 · Cited by 9
Scheeff, J., Rauss, K. S., & Schönenberg, M. (2021) · Progress in Neuro-Psychopharmacology and Biological Psychiatry · doi:10.1016/j.pnpbp.2021.110355 · Cited by 7
Schild, A., Volk, J., Scharfenberg, D., Schuermann, K., Meiberth, D. U., Onur, O. A., Jessen, F., & Maier, F. (2021) · Journal of Alzheimer s Disease · doi:10.3233/jad-201126 · Cited by 7
Lesions and reduced working memory impair emotion recognition in self and others
Neumann, R., Völker, J., Hajba, Z., & Seiler, S. (2021) · Cognition & Emotion · doi:10.1080/02699931.2021.1983521 · Cited by 7
Windmill Graph based Feature Descriptors for Facial Expression Recognition
Kartheek, M. N., Prasad, M. V. N. K., & Bhukya, R. (2022) · Optik · doi:10.1016/j.ijleo.2022.169053 · Cited by 7
Texture based feature extraction using symbol patterns for facial expression recognition
Kartheek, M. N., Prasad, M. V. N. K., & Bhukya, R. (2022) · Cognitive Neurodynamics · doi:10.1007/s11571-022-09824-z · Cited by 7
Construction and validation of the Dalian emotional movement open-source set (DEMOS)
Zhang, M., Yu, L., Zhang, K., Du, B., Zhan, B., Jia, S., Chen, S., Han, F., Li, Y., Liu, S., et al. (2022) · Behavior Research Methods · doi:10.3758/s13428-022-01887-4 · Cited by 7
Diržytė, A., Antanaitis, F., & Patapas, A. (2022) · Behavioral Sciences · doi:10.3390/bs12100351 · Cited by 12
Large-Scale Facial Expression Recognition Using Dual-Domain Affect Fusion for Noisy Labels
Neo, D., Chen, T., & WINKLER, S. S. (2023) · IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW) · doi:10.1109/cvprw59228.2023.00603 · Cited by 7
Vanderhasselt, M., Koster, E., Goubert, L., & de Raedt, R. (2012) · European Journal of Personality · doi:10.1002/per.846 · Cited by 7
Processing of Fear and Anger Facial Expressions: The Role of Spatial Frequency
Comfort, W. E., Wang, M., Benton, C. P., & Zana, Y. (2013) · Frontiers in Psychology · doi:10.3389/fpsyg.2013.00213 · Cited by 7
Zeev‐Wolf, M., & Rassovsky, Y. (2020) · Neuropsychologia · doi:10.1016/j.neuropsychologia.2020.107352 · Cited by 7
A influência da intensidade emocional no reconhecimento de emoções em faces por crianças brasileiras
Aguiar, J. S. R., Silva, A. I. D. P., Rocha, C., Alves, N. T., & de Souza, W. C. (2017) · Universitas Psychologica · doi:10.11144/javeriana.upsy15-5.iier · Cited by 7
Social feedback interferes with implicit rule learning: Evidence from event-related brain potentials
Beston, P. J., Barbet, C., Heerey, E. A., & Thierry, G. (2018) · Cognitive Affective & Behavioral Neuroscience · doi:10.3758/s13415-018-0635-z · Cited by 7
Identification of Primary Facial Emotions in Relation to Level of Self-Criticism
Strnádelová, B., Halamová, J., & Kanovský, M. (2019) · Perception · doi:10.1177/0301006619870399 · Cited by 7
Less is More: Pursuing the Visual Turing Test with the Kuleshov Effect
Gustavo Olague, A., Olague, M., Jacobo-Lopez, A. R., & Ibarra-Vázquez, G. (2021) · IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW) · doi:10.1109/cvprw53098.2021.00171 · Cited by 7
Crone, D. L., Bode, S., Murawski, C., & Laham, S. M. (2017) · PsyArXiv (OSF Preprints) · doi:10.31234/osf.io/sja3m · Cited by 7
Zhang, Z., Peng, Y., Jiang, Y., & Chen, T. (2023) · Behavior Research Methods · doi:10.3758/s13428-023-02168-4 · Cited by 7
Intact but Protracted Facial and Prosodic Emotion Recognition Among Autistic Adults
Jertberg, R., Begeer, S., Geurts, H. M., Chakrabarti, B., & der Burg, E. V. (2025) · Journal of Autism and Developmental Disorders · doi:10.1007/s10803-025-06786-z · Cited by 8
Stereoscopy Amplifies Emotions Elicited by Facial Expressions
Hakala, J., Kätsyri, J., & Häkkinen, J. P. (2015) · i-Perception · doi:10.1177/2041669515615071 · Cited by 6
Alexithymia and Facial Mimicry in Response to Infant and Adult Affect-Expressive Faces
Nordmann, M. A., Schäfer, R. B., Müller, T., & Franz, M. (2021) · Frontiers in Psychology · doi:10.3389/fpsyg.2021.635648 · Cited by 9
Vaıoulı, P., Panteli, M., & Panayiotou, G. (2021) · Current Psychology · doi:10.1007/s12144-021-02329-8 · Cited by 8
Hybrid pooling with wavelets for convolutional neural networks
Trevino-Sanchez, D., & Alarcon‐Aquino, V. (2022) · Journal of Intelligent & Fuzzy Systems · doi:10.3233/jifs-219223 · Cited by 6
Kryklywy, J. H., Ehlers, M. R., Beukers, A. O., Moore, S. R., Todd, R. M., & Anderson, A. K. (2022) · eNeuro · doi:10.1523/eneuro.0274-22.2022 · Cited by 6
Vanderhasselt, M., Sánchez-López, Á., Pulopulos, M. M., Razza, L. B., Smet, S. D., Brunoni, A. R., Baeken, C., Raedt, R. D., & Allaert, J. (2023) · International Journal of Clinical and Health Psychology · doi:10.1016/j.ijchp.2023.100384 · Cited by 6
Heimer, O., Kron, A., & Hertz, U. (2023) · Cognition · doi:10.1016/j.cognition.2023.105423 · Cited by 5
Development and validation of a natural dynamic facial expression stimulus set
Pasqualette, L. B. B. B., Klinger, S., & Kulke, L. (2023) · PLoS ONE · doi:10.1371/journal.pone.0287049 · Cited by 7
McCrackin, S. D., Provencher, S., Mendell, E., & Ristic, J. (2023) · Social Cognition · doi:10.1521/soco.2023.41.4.365 · Cited by 8
The effect of aging and emotions on time processing
Malva, P. L., Prete, G., Crosta, A. D., Ceccato, I., Mammarella, N., Palumbo, R., & Domenico, A. D. (2023) · Aging Clinical and Experimental Research · doi:10.1007/s40520-023-02563-z · Cited by 8
The Influence of Naturalness, Attractiveness and Intensity on Facial Emotion Recognition
Limbrecht, K., Rukavina, S., Scheck, A., Walter, S., Hoffmann, H., & Traue, H. C. (2012) · Journal of Psychology Research · doi:10.17265/2159-5542/2012.03.004 · Cited by 7
Grol, M., & Raedt, R. D. (2014) · Cognition & Emotion · doi:10.1080/02699931.2014.895299 · Cited by 6
Emotional see-saw affects rationality of decision-making: Evidence for metacognitive impairments
Folwarczny, M., Kaczmarek, M. C., Doliński, D., & Szczepanowski, R. (2018) · Acta Psychologica · doi:10.1016/j.actpsy.2018.04.012 · Cited by 6
Filter pruning by image channel reduction in pre-trained convolutional neural networks
Chung, G. S., & Won, C. S. (2020) · Multimedia Tools and Applications · doi:10.1007/s11042-020-09373-9 · Cited by 6
A Simple Yet Effective Convolutional Neural Network Model to Classify Facial Expressions
Sari, M., Moussaouı, A., & Hadid, A. (2020) · Lecture notes in networks and systems · doi:10.1007/978-3-030-58861-8_14 · Cited by 6
Pain modulation by your partner: An experimental investigation from a social-affective perspective
Hillmer, K., Kappesser, J., & Hermann, C. (2021) · PLoS ONE · doi:10.1371/journal.pone.0254069 · Cited by 6
Pictures of Facial Affect-Ulm (PFA-U): A New Facs-Based set of Pictures for Basic Emotions
Limbrecht-Ecklundt, K., Hoffmann, H., Walter, S., Gruss, S., Hrabal, D., & Traue, H. C. (2013) · Emerald Group Publishing Limited eBooks · doi:10.1108/s1746-9791(2013)0000009011 · Cited by 6
Affective Influence on Context-Specific Proportion Congruent (CSPC) Effect
Zhang, J., Kiesel, A., & Dignath, D. (2019) · Experimental Psychology (formerly Zeitschrift für Experimentelle Psychologie) · doi:10.1027/1618-3169/a000436 · Cited by 6
Research of Facial Expression Recognition Based on Deep Learning
Zhang, L., Yang, Y., Li, W., Dang, S., & Zhu, M. (2018) · IEEE International Conference on Software Engineering and Service Science (ICSESS) · doi:10.1109/icsess.2018.8663777 · Cited by 6
The effect of ethnicity and team membership on face processing: a cultural neuroscience perspective
Yan, Z., Schmidt, S. N. L., Saur, S., Kirsch, P., & Mier, D. U. (2019) · Social Cognitive and Affective Neuroscience · doi:10.1093/scan/nsz083 · Cited by 6
Weighted Ensemble Based on Prisoner Dilemma for Facial Expression Recognition
Hunafa, M. H., Ramadhan, M. M. L., Ramadhan, A. W., Rachmadi, M. F., & Jatmiko, W. (2025) · IEEE Access · doi:10.1109/access.2025.3582643 · Cited by 5
Verheyen, L., van Engelen, B., Winkens, B., Vanbrabant, K., Hannes, E., Nawrot, T. S., Malina, R. M., van Schayck, O. C. P., & Plusquin, M. (2025) · Frontiers in Public Health · doi:10.3389/fpubh.2025.1620199 · Cited by 6
Chess pattern with different weighting schemes for person independent facial expression recognition
Kartheek, M. N., Prasad, M. V. N. K., & Bhukya, R. (2021) · Multimedia Tools and Applications · doi:10.1007/s11042-021-11270-8 · Cited by 5
Rhythmic Information Sampling in the Brain during Visual Recognition
Caplette, L., Jerbi, K., & Gosselin, F. (2023) · Journal of Neuroscience · doi:10.1523/jneurosci.1838-22.2023 · Cited by 5
Wu, Y., Li, D., Chen, X., Tang, Y., & Huang, S. (2024) · Multimedia Systems · doi:10.1007/s00530-023-01227-2 · Cited by 5
Metadata
- Authors
- Goeleven, E., De Raedt, R., Leyman, L., & Verschuere, B.
- Affiliations
- Ghent University (BE)
- Venue
- Cognition & Emotion
- Publisher
- Informa UK Limited
- Published
- 2008-09
- Volume
- 22
- Issue
- 6
- Pages
- 1094-1118
- ISSN
- 0269-9931 (ISSN-L)
- 1464-0600
- OpenAlex
- W2042333532
- Cited by
- 793
- References
- 26
- Citations by year
- 2026: 30 · 2025: 48 · 2024: 58 · 2023: 59 · 2022: 82 · 2021: 76 · 2020: 68 · 2019: 50 · 2018: 46 · 2017: 41 · 2016: 32 · 2015: 36 · 2014: 33 · 2013: 40 · 2012: 30
- FWCI
- 10.03
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- Cognition & Emotion (publishedVersion)
- Ghent University Academic Bibliography (Ghent University) (submittedVersion)
- Topics
- Life Sciences › Neuroscience › Cognitive Neuroscience › Face Recognition and Perception
- Physical Sciences › Computer Science › Artificial Intelligence › Emotion and Mood Recognition
- Physical Sciences › Computer Science › Computer Vision and Pattern Recognition › Face and Expression Recognition
- Keywords
- KDEF, emotion recognition, stimulus validation, emotional intensity, arousal ratings, basic emotions
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