J. N. Bassili 1979 Emotion recognition: the role of facial movement and the relative importance of upper and lower areas of the face Journal of personality and social psychology 37 11 2049 2058
D. BombariP. C. SchmidM. Schmid MastS. BirriF. W. MastJ. S. Lobmaier 2013 Emotion recognition: The role of featural and configural face information Quarterly Journal of Experimental Psychology 66 12 2426 2442 doi:10.1080/17470218.2013.789065
A. J. CalderJ. KeaneA. W. YoungM. Dean 2000 Configural information in facial expression perception Journal of Experimental Psychology: Human Perception and Performance 26 2 527 551
M. G. CalvoD. Lundqvist 2008 Facial expressions of emotion (KDEF): Identification under different display-duration conditions Behavior Research Methods 40 1 109 115 doi:10.3758/BRM.40.1.109
M. G. CalvoL. Nummenmaa 2009 Eye-movement assessment of the time course in facial expression recognition: Neurophysiological implications Cognitive, Affective and Behavioral Neuroscience 9 4 398 411 doi:10.3758/CABN.9.4.398
M. G. CalvoL. Nummenmaa 2016 Perceptual and affective mechanisms in facial expression recognition: An integrative review. [Article] Cognition and Emotion 30 6 1081 1106 doi:10.1080/02699931.2015.1049124
D. CireşanU. MeierJ. Schmidhuber 2012 „Multi-column Deep Neural Networks for Image Classification‟ February doi: 10.1109/CVPR.2012.6248110
K. ClawsonL. S. DelicatoS. Garfield 2017 Automated Representation of Non-Emotional Expressivity to Facilitate Understanding of Facial Mobility: Preliminary Findings Intelligent Systems Conference 7th – 8th September London 2017 doi: 10.1109/IntelliSys.2017.8324218
P. R. Dachapally 2017 „Facial Emotion Detection Using Convolutional Neural Networks and Representational Autoencoder Units‟ Available at: http://arxiv.org/ftp/arxiv/papers/1706/1706.01509.pdf%0Ahttp://arxiv.org/abs/1706.01509
L. S. DelicatoJ. FinnJ. MorrisB. Smith 2014 Increased sensitivity to happy compared with fearful faces in a temporal two-interval forced-choice paradigm European Conference on Visual Perception, Belgrade, Serbia. Perception 43 1 75 doi: 10.1177/03010066140430S10
L. S. DelicatoR. Mason 2015 Happiness is in the mouth of the beholder and fear in the eyes Vision Sciences Society, St. Petes Beach, Florida, US. Journal of Vision 15 1378 doi:10.1167/15.12.1378
L. S DelicatoJ. WincenciakD. J. Burn 2016 Evidence for a Face Inversion Effect in People with Parkinson‟s Perception 45 S2 295 doi: 10.1177/0301006616671273
J.W. EllisonD.W. Massaro 1997 Featural evaluation, integration, and judgment of facial affect. Journal of Experimental Psychology: Human Perception and Performance 23 1 213
H. Jung 2015 „Development of deep learning-based facial expression recognition system‟ 2015 Frontiers of Computer Vision, FCV 2015 2 5 doi: 10.1109/FCV.2015.7103729
M. S. Keil 2008 „Preferred spatial frequencies for human face processing are associated with optimal class discrimination in the machine‟ PLoS ONE 3 7 1 5 doi: 10.1371/journal.pone.0002590
B.-K. Kim 2016 „Hierarchical committee of deep convolutional neural networks for robust facial expression recognition‟ Journal on Multimodal User Interfaces. Springer Berlin Heidelberg 10 2 173 189 doi: 10.1007/s12193-015-0209-0
Y. LecunL. BottouY. BengioP. Haffner Gradient-based Learn. Appl. Doc. Recognit. 86 11 1998 2278 2324 http://dx.doi.org/10.1109/5.726791
K. LiuM. ZhangZ. Pan 2016 „Facial Expression Recognition with CNN Ensemble‟ Proceedings - 2016 International Conference on Cyberworlds, CW 2016 163 166 doi: 10.1109/CW.2016.34
A. T. Lopes 2017 „Facial expression recognition with Convolutional Neural Networks: Coping with few data and the training sample order‟ Pattern Recognition. Elsevier 61 610 628 doi: 10.1016/j.patcog.2016.07.026
A. T. LopesE. De AguiarT. Oliveira-Santos 2015 „A Facial Expression Recognition System Using Convolutional Networks‟ Brazilian Symposium of Computer Graphic and Image Processing, 2015–Octob 273 280 doi: 10.1109/SIBGRAPI.2015.14
P. Lucey 2010 „The extended Cohn-Kanade dataset (CK+): A complete dataset for action unit and emotion-specified expression‟ 2010 IEEE Computer Society Conference on Computer Vision and Pattern Recognition - Workshops, CVPRW 2010 May 94 101 doi: 10.1109/CVPRW.2010.5543262
M. LyonsS. Akamatsu 1998 „Coding Facial Expressions with GaborWavelets‟ third IEEE Conference on Automatic Face and Gesture Recognition 200 205 doi: 10.1109/AFGR.1998.670949
D. MartinG. SlessorR. AllenL.H. PhillipsS. Darling 2012 Processing orientation and emotion recognition. Emotion 12 1 39
D. MatsumotoH. C. Hwang 2014 Judgments of subtle facial expressions of emotion Emotion 14 349 357 http://dx.doi.org/10.1037/a0035237
A. MollahosseiniD. ChanM. H. Mahoor 2015 „Going Deeper in Facial Expression Recognition using Deep Neural Networks‟ doi: 10.1109/WACV.2016.7477450
N. Mousavi 2016 „Understanding how deep neural networks learn face expressions‟ Proceedings of the International Joint Conference on Neural Networks, 2016–Octob 227 234 doi: 10.1109/IJCNN.2016.7727203
R. PalermoM. Coltheart 2004 Photographs of facial expression: Accuracy, response times, and ratings of intensity Behavior Research Methods, Instruments & Computers 36 634 638 http://dx.doi.org/10.3758/BF03206544
C. PramerdorferM. Kampel 2016 „Facial Expression Recognition using Convolutional Neural Networks: State of the Art‟ Available at: http://arxiv.org/abs/1612.02903
A. RaghuvanshiV. Choksi 2016 „Facial Expression Recognition with Convolutional Neural Networks‟ 1 8
G. RecioA. SchachtW. Sommer 2014 Recognizing dynamic facial expressions of emotion: Specificity and intensity effects in event-related brain potentials. Biological psychology 96 111 125
K. Shan 2017 „Automatic Facial Expression Recognition Based on a Deep Convolutional-Neural-Network Structure‟ IEEE Computer Society 123 128
Y. SunX. WangX. Tang 2014 „Deep Learning Face Representation from Predicting 10 , 000 Classes‟
S. XieH. Hu 2017 „Facial expression recognition with FRR-CNN‟ Electronics Letters 53 4 235 237 doi: 10.1049/el.2016.4328
Z. Yu 2015 „Image based Static Facial Expression Recognition with Multiple Deep Network Learning‟ ACM on International Conference on Multimodal Interaction - ICMI 435 442 doi: 10.1145/2823327.2823341