21.3.6.2.1 Emotion Recognition, Deep Learning

Chapter Contents (Back)
Emotion Recognition. Deep Learning.

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

Nguyen, D.[Dung], Nguyen, K.[Kien], Sridharan, S.[Sridha], Dean, D.[David], Fookes, C.[Clinton],
Deep spatio-temporal feature fusion with compact bilinear pooling for multimodal emotion recognition,
CVIU(174), 2018, pp. 33-42.
Elsevier DOI 1812
BibRef

Nguyen, D.[Dung], Nguyen, K.[Kien], Sridharan, S.[Sridha], Ghasemi, A.[Afsane], Dean, D.[David], Fookes, C.[Clinton],
Deep Spatio-Temporal Features for Multimodal Emotion Recognition,
WACV17(1215-1223)
IEEE DOI 1609
Convolution, Emotion recognition, Face, Feature extraction, Speech, Speech recognition, Streaming, media 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], Rehman, A.U.[Ateeq Ur], 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


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

Ranganathan, H., Chakraborty, S., Panchanathan, S.,
Multimodal emotion recognition using deep learning architectures,
WACV16(1-9)
IEEE DOI 1606
Databases 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:May 2, 2021 at 12:04:43