22.3.6.2.1 Emotion Recognition, Deep Learning

Chapter Contents (Back)
Emotion Recognition. Learning. Deep Learning.

Sanchez-Mendoza, D.[David], Masip, D.[David], Lapedriza, A.[Agata],
Emotion recognition from mid-level features,
PRL(67, Part 1), No. 1, 2015, pp. 66-74.
Elsevier DOI 1511
Facial expression BibRef

Pons, G.[Gerard], Masip, D.[David],
Multitask, Multilabel, and Multidomain Learning With Convolutional Networks for Emotion Recognition,
Cyber(52), No. 6, June 2022, pp. 4764-4771.
IEEE DOI 2207
Task analysis, Emotion recognition, Training, Image recognition, Face recognition, Deep learning, multitask learning BibRef

Kaya, H.[Heysem], Gürpinar, F.[Furkan], Salah, A.A.[Albert Ali],
Video-based emotion recognition in the wild using deep transfer learning and score fusion,
IVC(65), No. 1, 2017, pp. 66-75.
Elsevier DOI 1709
EmotiW BibRef

Kim, H., Kim, Y., Kim, S.J., Lee, I.,
Building Emotional Machines: Recognizing Image Emotions Through Deep Neural Networks,
MultMed(20), No. 11, November 2018, pp. 2980-2992.
IEEE DOI 1810
Feature extraction, Emotion recognition, Machine learning, Predictive models, Databases, Task analysis, Psychology, deep network BibRef

Lingenfelser, F., Wagner, J., Deng, J., Brueckner, R., Schuller, B., André, E.,
Asynchronous and Event-Based Fusion Systems for Affect Recognition on Naturalistic Data in Comparison to Conventional Approaches,
AffCom(9), No. 4, October 2018, pp. 410-423.
IEEE DOI 1812
Hidden Markov models, Emotion recognition, Recurrent neural networks, Visualization, Heuristic algorithms, deep learning BibRef

Jain, N.[Neha], Kumar, S.[Shishir], Kumar, A.[Amit], Shamsolmoali, P.[Pourya], Zareapoor, M.[Masoumeh],
Hybrid deep neural networks for face emotion recognition,
PRL(115), 2018, pp. 101-106.
Elsevier DOI 1812
Emotion recognition, Deep learning, Recurrent neural networks, Convolutional Neural Networks, Hybrid CNN-RNN BibRef

Jain, D.K.[Deepak Kumar], Shamsolmoali, P.[Pourya], Sehdev, P.[Paramjit],
Extended deep neural network for facial emotion recognition,
PRL(120), 2019, pp. 69-74.
Elsevier DOI 1904
Facial emotion recognition, Deep neural network, Fully convolution network BibRef

Li, S.[Shan], Deng, W.H.[Wei-Hong],
Blended Emotion in-the-Wild: Multi-label Facial Expression Recognition Using Crowdsourced Annotations and Deep Locality Feature Learning,
IJCV(127), No. 6-7, June 2019, pp. 884-906.
Springer DOI 1906
BibRef
Earlier:
Deep Emotion Transfer Network for Cross-database Facial Expression Recognition,
ICPR18(3092-3099)
IEEE DOI 1812
Databases, Face recognition, Kernel, Training, Task analysis, Testing BibRef

Zhang, W., He, X., Lu, W.,
Exploring Discriminative Representations for Image Emotion Recognition With CNNs,
MultMed(22), No. 2, February 2020, pp. 515-523.
IEEE DOI 2001
Image emotion classification, discriminative representation, emotional inference, deep learning, convolutional neural networks BibRef

Tian, Y., Cheng, J., Li, Y., Wang, S.,
Secondary Information Aware Facial Expression Recognition,
SPLetters(26), No. 12, December 2019, pp. 1753-1757.
IEEE DOI 2001
emotion recognition, face recognition, image classification, learning (artificial intelligence), SIFE-Net, FER datasets, deep learning BibRef

Naqvi, R.A.[Rizwan Ali], Arsalan, M.[Muhammad], Rehman, A.[Abdul], Ur Rehman, A.[Ateeq], Loh, W.K.[Woong-Kee], Paul, A.[Anand],
Deep Learning-Based Drivers Emotion Classification System in Time Series Data for Remote Applications,
RS(12), No. 3, 2020, pp. xx-yy.
DOI Link 2002
BibRef

Parthasarathy, S.[Srinivas], Busso, C.[Carlos],
Predicting Emotionally Salient Regions Using Qualitative Agreement of Deep Neural Network Regressors,
AffCom(12), No. 2, April 2021, pp. 402-416.
IEEE DOI 2106
Emotion recognition, Market research, Databases, Affective computing, Speech recognition, Task analysis, regressors of attribute-based descriptors BibRef

Kollias, D.[Dimitrios], Zafeiriou, S.P.[Stefanos P.],
Exploiting Multi-CNN Features in CNN-RNN Based Dimensional Emotion Recognition on the OMG in-the-Wild Dataset,
AffCom(12), No. 3, July 2021, pp. 595-606.
IEEE DOI 2109
Feature extraction, Estimation, Databases, Computer architecture, Visualization, Machine learning, Emotion recognition, OMG-Emotion database and challenge
See also OMG-Emotion (One-Minute Gradual-Emotional Behavior). BibRef

Al Chanti, D.[Dawood], Caplier, A.[Alice],
Deep Learning for Spatio-Temporal Modeling of Dynamic Spontaneous Emotions,
AffCom(12), No. 2, April 2021, pp. 363-376.
IEEE DOI 2106
Spatiotemporal phenomena, Visualization, Face recognition, Face, Videos, Machine learning, Computational modeling, 3D-CNN, ConvLSTM, spatiotemporal features BibRef

Zhang, H.[Haimin], Xu, M.[Min],
Weakly Supervised Emotion Intensity Prediction for Recognition of Emotions in Images,
MultMed(23), 2021, pp. 2033-2044.
IEEE DOI 2107
Emotion recognition, Streaming media, Visualization, Feature extraction, Neural networks, Semantics, Annotations, deep neural networks BibRef

Hariri, W.[Walid], Farah, N.[Nadir],
Recognition of 3D emotional facial expression based on handcrafted and deep feature combination,
PRL(148), 2021, pp. 84-91.
Elsevier DOI 2107
Facial emotion, CNN, Deep covariance, Manifold, Gaussian kernel
See also 3D face recognition using covariance based descriptors. BibRef

Yang, J.Y.[Jing-Yuan], Li, J.[Jie], Wang, X.M.[Xiu-Mei], Ding, Y.X.[Yu-Xuan], Gao, X.B.[Xin-Bo],
Stimuli-Aware Visual Emotion Analysis,
IP(30), 2021, pp. 7432-7445.
IEEE DOI 2109
Feature extraction, Visualization, Psychology, Task analysis, Image color analysis, Face recognition, Deep learning, convolutional neural networks BibRef

Oveneke, M.C.[Meshia Cédric], Zhao, Y.[Yong], Pei, E.[Ercheng], Berenguer, A.D.[Abel Díaz], Jiang, D.M.[Dong-Mei], Sahli, H.[Hichem],
Leveraging the Deep Learning Paradigm for Continuous Affect Estimation from Facial Expressions,
AffCom(13), No. 1, January 2022, pp. 426-439.
IEEE DOI 2203
Deep learning, Estimation, Face recognition, Face, Feature extraction, Training, Kalman filters, Affect estimation, extended kalman filtering BibRef

Akhtar, M.S.[Md Shad], Ghosal, D.[Deepanway], Ekbal, A.[Asif], Bhattacharyya, P.[Pushpak], Kurohashi, S.[Sadao],
All-in-One: Emotion, Sentiment and Intensity Prediction Using a Multi-Task Ensemble Framework,
AffCom(13), No. 1, January 2022, pp. 285-297.
IEEE DOI 2203
Task analysis, Hidden Markov models, Sentiment analysis, Deep learning, Computational modeling, Predictive models, ensemble BibRef

Avola, D.[Danilo], Cinque, L.[Luigi], Fagioli, A.[Alessio], Foresti, G.L.[Gian Luca], Massaroni, C.[Cristiano],
Deep Temporal Analysis for Non-Acted Body Affect Recognition,
AffCom(13), No. 3, July 2022, pp. 1366-1377.
IEEE DOI 2209
Feature extraction, Emotion recognition, Task analysis, Games, Pain, Skeleton, Non-acted affective computing, body movement, long short-term memory (LSTM) BibRef

Dias, W.[William], Andaló, F.[Fernanda], Padilha, R.[Rafael], Bertocco, G.[Gabriel], Almeida, W.[Waldir], Costa, P.[Paula], Rocha, A.[Anderson],
Cross-dataset emotion recognition from facial expressions through convolutional neural networks,
JVCIR(82), 2022, pp. 103395.
Elsevier DOI 2201
Emotion recognition, Facial analysis, Cross-dataset evaluation, Deep learning BibRef

Barros, P.[Pablo], Barakova, E.[Emilia], Wermter, S.[Stefan],
Adapting the Interplay Between Personalized and Generalized Affect Recognition Based on an Unsupervised Neural Framework,
AffCom(13), No. 3, July 2022, pp. 1349-1365.
IEEE DOI 2209
Emotion recognition, Adaptation models, Computational modeling, Deep learning, Data models, Feature extraction, Convolution, continual learning BibRef

Song, P.P.[Pei-Pei], Guo, D.[Dan], Cheng, J.[Jun], Wang, M.[Meng],
Contextual Attention Network for Emotional Video Captioning,
MultMed(25), 2023, pp. 1858-1867.
IEEE DOI 2306
Visualization, Feature extraction, Task analysis, Emotion recognition, Convolutional neural networks, Semantics, attention BibRef

Song, P.P.[Pei-Pei], Guo, D.[Dan], Yang, X.[Xun], Tang, S.G.[Shen-Geng], Wang, M.[Meng],
Emotional Video Captioning With Vision-Based Emotion Interpretation Network,
IP(33), 2024, pp. 1122-1135.
IEEE DOI 2402
Visualization, Vocabulary, Psychology, Task analysis, Generators, Emotion recognition, Wheels, Emotional video captioning, emotion-fact coordinated optimization BibRef

Zheng, J.H.[Jia-Hao], Zhang, S.[Sen], Wang, Z.[Zilu], Wang, X.P.[Xiao-Ping], Zeng, Z.G.[Zhi-Gang],
Multi-Channel Weight-Sharing Autoencoder Based on Cascade Multi-Head Attention for Multimodal Emotion Recognition,
MultMed(25), 2023, pp. 2213-2225.
IEEE DOI 2306
Feature extraction, Emotion recognition, Data models, Training, Task analysis, Decoding, Data mining, multi-head attention mechanism BibRef

Zhang, C.J.[Chun-Jiong], Li, M.Y.[Ming-Yong], Wu, D.[Di],
Federated Multidomain Learning With Graph Ensemble Autoencoder GMM for Emotion Recognition,
ITS(24), No. 7, July 2023, pp. 7631-7641.
IEEE DOI 2307
Face recognition, Task analysis, Collaborative work, Data models, Image recognition, Adaptation models, Training, domain adaptability BibRef

Liu, D.J.[Dong-Jun], Dai, W.C.[Wei-Chen], Zhang, H.K.[Hang-Kui], Jin, X.Y.[Xuan-Yu], Cao, J.T.[Jian-Ting], Kong, W.Z.[Wan-Zeng],
Brain-Machine Coupled Learning Method for Facial Emotion Recognition,
PAMI(45), No. 9, September 2023, pp. 10703-10717.
IEEE DOI 2309
BibRef

Sherly-Alphonse, A., Abinaya, S., Abirami, S.,
Alibaba and forty thieves algorithm and novel Prioritized Prewitt Pattern(PPP)-based convolutional neural network (CNN) using hyperspherically compressed weights for facial emotion recognition,
JVCIR(97), 2023, pp. 103948.
Elsevier DOI 2312
Optimization, CNN, Weights, Emotion, Hyperparameters BibRef

Wu, Y.J.[Yu-Jin], Daoudi, M.[Mohamed], Amad, A.[Ali],
Transformer-Based Self-Supervised Multimodal Representation Learning for Wearable Emotion Recognition,
AffCom(15), No. 1, January 2024, pp. 157-172.
IEEE DOI 2403
Emotion recognition, Task analysis, Physiology, Feature extraction, Data models, Transformers, Self-supervised learning, transformers BibRef


Nagappan, S.[Sidharrth], Tan, J.Q.[Jia Qi], Wong, L.K.[Lai-Kuan], See, J.[John],
Context-Aware Multi-Stream Networks for Dimensional Emotion Prediction in Images,
ICIP23(2480-2484)
IEEE DOI 2312
BibRef

Zell, A.[Adina], Sumbul, G.[Gencer], Demir, B.[Begüm],
Deep Metric Learning-Based Semi-Supervised Regression with Alternate Learning,
ICIP22(2411-2415)
IEEE DOI 2211
Training, Emotion recognition, Parameter estimation, Codes, Neural networks, Deep architecture, Semi-supervised regression, deep learning BibRef

Jeong, E.[Euiseok], Oh, G.[Geesung], Lim, S.[Sejoon],
Multi-task Learning for Human Affect Prediction with Auditory-Visual Synchronized Representation,
ABAW22(2437-2444)
IEEE DOI 2210
Deep learning, Visualization, Annotations, Predictive models, Feature extraction, Multitasking, Data models BibRef

Khan, A.S.[Ahmed Shehab], Li, Z.Y.[Zhi-Yuan], Cai, J.[Jie], Tong, Y.[Yan],
Regional Attention Networks with Context-aware Fusion for Group Emotion Recognition,
WACV21(1149-1158)
IEEE DOI 2106
Visualization, Emotion recognition, Sentiment analysis, Fuses, Computational modeling, Pressing, Streaming media BibRef

Peña, A., Morales, A., Serna, I., Fierrez, J., Lapedriza, A.,
Facial Expressions as a Vulnerability in Face Recognition,
ICIP21(2988-2992)
IEEE DOI 2201
Image recognition, Databases, Face recognition, Genetic expression, Detectors, Security, Face Recognition, Expression BibRef

Peña, A.[Alejandro], Fierrez, J.[Julian], Morales, A.[Aythami], Lapedriza, A.[Agata],
Learning Emotional-Blinded Face Representations,
ICPR21(3566-3573)
IEEE DOI 2105
Emotion recognition, Privacy, Face recognition, Process control, Regulation, Emotional responses, Task analysis BibRef

Gund, M.[Manasi], Bharadwaj, A.R.[Abhiram Ravi], Nwogu, I.[Ifeoma],
Interpretable Emotion Classification Using Temporal Convolutional Models,
ICPR21(6367-6374)
IEEE DOI 2105
Convolutional codes, Analytical models, Pain, Face recognition, Neural networks, Predictive models, Encoding BibRef

Aledhari, M.[Mohammed], Razzak, R.[Rehma], Parizi, R.M.[Reza M.], Srivastava, G.[Gautam],
Deep Neural Networks for Detecting Real Emotions Using Biofeedback and Voice,
HCAU20(302-309).
Springer DOI 2103
BibRef

Prawiro, H., Pan, T.Y., Hu, M.C.,
An Empirical Study of Emotion Recognition from Thermal Video Based on Deep Neural Networks,
VCIP20(407-410)
IEEE DOI 2102
Emotion recognition, Solid modeling, Gray-scale, Convolution, deep neural network BibRef

Ozkan, S., Akar, G.B.,
Relaxed Spatio-Temporal Deep Feature Aggregation for Real-Fake Expression Prediction,
EmotionComp17(3094-3100)
IEEE DOI 1802
Computational modeling, Computer architecture, Data models, Face, Feature extraction, Robustness, Visualization BibRef

Moghadam, S.M., Seyyedsalehi, S.A.,
Nonlinear analysis of video images using deep recurrent auto-associative neural networks for facial understanding,
IPRIA17(20-25)
IEEE DOI 1712
emotion recognition, face recognition, feature extraction, image sequences, learning (artificial intelligence), Nonlinear Video Analysis BibRef

Kim, B.K., Dong, S.Y., Roh, J., Kim, G., Lee, S.Y.,
Fusing Aligned and Non-aligned Face Information for Automatic Affect Recognition in the Wild: A Deep Learning Approach,
Affect16(1499-1508)
IEEE DOI 1612
BibRef

Khorrami, P., Le Paine, T., Brady, K., Dagli, C., Huang, T.S.,
How deep neural networks can improve emotion recognition on video data,
ICIP16(619-623)
IEEE DOI 1610
Convolution BibRef

Deng, W., Hu, J., Zhang, S., Guo, J.,
DeepEmo: Real-world facial expression analysis via deep learning,
VCIP15(1-4)
IEEE DOI 1605
Databases BibRef

Chen, M.[Ming], Zhang, L.[Lu], Allebach, J.P.[Jan P.],
Learning deep features for image emotion classification,
ICIP15(4491-4495)
IEEE DOI 1512
Image emotion BibRef

Chapter on Face Recognition, Detection, Tracking, Gesture Recognition, Fingerprints, Biometrics continues in
Emotion Recognition, Survey, General, Review, Datasets, Database .


Last update:Apr 10, 2024 at 09:54:40