Mobile QR Code QR CODE

※ The user interface design of www.ieiespc.org has been recently revised and updated. Please contact inter@theieie.org for any inquiries regarding paper submission.

Journal Search

  1. Home
  2. Archive
  3. 2024-02 (Vol.13 No.01)
  4. 10.5573/IEIESPC.2024.13.1.61
XML PDF INFO REF

REFERENCES

1 
E.S. Salama, R.A. El-Khoribi, M.E. Shoman, M.A.W. Shalaby, ``A 3D-convolutional neural network framework with ensemble learning techniques for multi-modal emotion recognition.'' Egyptian Informatics Journal, vol. 22, no. 2, pp. 167-176. 2021.DOI
2 
Y. Wu, J. Li, ``Multi-modal emotion identification fusing facial expression and EEG.'' Multimedia Tools and Applications, vol. 82, no. 7, pp. 10901-10919. 2023.DOI
3 
L. Fang, S.P. Xing, Z. Ma, Z. Zhang, Y. Long, K.P. Lee, S.J. Wang, ``Emo-MG Framework: LSTM-based Multi-modal Emotion Detection through Electro encephalography Signals and Micro Gestures.'' International Journal of Human-Computer Interaction, vol. 1, no. 1, pp. 1-17. 2023.DOI
4 
F. H. Shajin, B. Aruna Devi, N. B. Prakash, G. R. Sreekanth, P. Rajesh, ``Sailfish optimizer with Levy flight, chaotic and opposition-based multi-level thres holding for medical image segmentation.'' Soft Computing, pp. 1-26. Apr. 2023.DOI
5 
F. H. Shajin, P. Rajesh, M. R. Raja, ``An efficient VLSI architecture for fast motion estimation exploiting zero motion pre judgment technique and a new quadrant-based search algorithm in HEVC.'' Circuits, Systems, and Signal Processing, pp. 1-24. Mar. 2022.DOI
6 
P. Rajesh, F. Shajin, ``A multi-objective hybrid algorithm for planning electrical distribution system.'' European Journal of Electrical Engineering, vol. 22, no. 4-5, pp. 224-509. Jun. 2020.DOI
7 
P. Rajesh, R. Kannan, J. Vishnupriyan, B. Rajani, ``Optimally detecting and classifying the transmission line fault in power system using hybrid technique.'' ISA transactions, vol. 130, pp. 253-264. Nov. 2022.DOI
8 
F.M. Alamgir, M.S. Alam, ``Hybrid multi-modal emotion recognition framework based on Inception V3 DenseNet.'' Multimedia Tools and Applications, vol. 1, no. 1, pp. 1-28. 2023.DOI
9 
S. Dutta, B.K.. Mishra, A. Mitra, A. Chakraborty, ``A Multi-modal Approach for Emotion Recognition Through the Quadrants of Valence-Arousal Plane.'' SN Computer Science, vol. 4, no. 5, pp. 460. 2023.DOI
10 
S. Liu, P. Gao, Y. Li, W. Fu, W. ``Ding, Multi-modal fusion network with complementarity and importance for emotion recognition.'' Information Sciences, vol. 619, no. 1, pp. 679-694. 2023.DOI
11 
J.M. Zhang, X. Yan, Z.Y. Li, L.M. Zhao, Y.Z. Liu, H.L. Li, B.L. Lu. ``A Cross-subject and Cross-modal Model for Multimodal Emotion Recognition''. InNeural Information Processing: 28th International Conference, ICONIP 2021, Sanur, Bali, Indonesia, December 8-12, Proceedings, Part VI 28 2021 (pp. 203-211). Springer International Publishing. 2021.DOI
12 
Z. Zhao, Z. Gong, M. Niu, J. Ma, H. Wang, Z. Zhang, Y. Li. ``Automatic respiratory sound classification via multi-branch temporal convolutional network'' InICASSP 2022-2022 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP) (pp. 9102-9106). IEEE. 2022.DOI
13 
Q. Wang, M. Wang, Y. Yang, X .Zhang. ``Multi-modal emotion recognition using EEG and speech signals.'' Computers in Biology and Medicine. vol. 149: 105907. 2022.DOI
14 
Y. Wang, S. Qiu, D. Li, C. Du, B.L. Lu, H. He. ``Multi-modal domain adaptation variational auto encoder for eeg-based emotion recognition.'' IEEE/CAA Journal of Automatica Sinica. vol. 9(9): 161226. 2022.DOI
15 
M. Maithri, U. Raghavendra, A. Gudigar, J. Samanth, P.D. Barua, M. Murugappan, Y. Chakole, U.R. Acharya, ``Automated emotion recognition: Current trends and future perspectives.'' Computer methods and programs in biomedicine, vol. 215, no. 1, p. 106646. 2022.DOI
16 
C. Guanghui, Z. Xiaoping, ``Multi-modal emotion recognition by fusing correlation features of speech-visual.'' IEEE Signal Processing Letters, vol. 28, pp. 533-537. 2021.DOI
17 
Y. Hu, F. Wang, ``Multi-Modal Emotion Recognition Combining Face Image and EEG Signal.'' Journal of Circuits, Systems and Computers, vol. 32, no. 07, p. 2350125. 2023.DOI
18 
M. Wang, Z. Huang, Y. Li, L. Dong, H. Pan, ``Maximum weight multi-modal information fusion algorithm of electro encephalographs and face images for emotion recognition.'' Computers & Electrical Engineering, vol. 94, no. 1, p. 107319. 2021.DOI
19 
Y. Zhang, C. Cheng, Y. Zhang, ``Multimodal emotion recognition using a hierarchical fusion convolutional neural network.'' IEEE access, vol. 9, no. 1, pp. 7943-7951. 2021.DOI
20 
D. Liu, L. Chen, Z. Wang, G. Diao, ``Speech expression multimodal emotion recognition based on deep belief network.'' Journal of Grid Computing, vol. 19, no. 2, p. 22. 2021.DOI
21 
H. Zhang, ``Expression-EEG based collaborative multimodal emotion recognition using deep autoencoder.'' IEEE Access, vol. 8, no. 1 pp. 164130-164143, 2020.DOI
22 
F. Aldosari, L. Abualigah, and K.H. Almotairi, ``A normal distributed dwarf mongoose optimization algorithm for global optimization and data clustering applications.'' Symmetry, vol. 14, no. 5, pp. 1021. 2022.DOI
23 
D. Saisanthiya, P. Supraja. "Heterogeneous Convolutional Neural Networks for Emotion Recognition Combined with Multimodal Factorised Bilinear Pooling and Mobile Application Recommendation", International Journal of Interactive Mobile Technologies (iJIM), 2023.DOI
24 
M. Park, and S. Chai, BTIMFL: A Blockchain-Based Trust Incentive Mechanism in Federated Learning. In International Conference on Computational Science and Its Applications (pp. 175-185). Cham: Springer Nature Switzerland, vol. 1, no. 1, pp. 1 June. 2023.DOI
25 
H. Zhang, ``Expression-EEG based collaborative multimodal emotion recognition using deep auto encoder.'' IEEE Access, vol. 8, no. 1, pp. 164130-164143. 2020.DOI
26 
J.O. Agushaka, A.E. Ezugwu, L. Abualigah, ``Dwarf mongoose optimization algorithm.'' Computer methods in applied mechanics and engineering, vol. 391, no. 1, p. 114570. 2022.DOI
27 
L.K.. Pavithra, T. Sree Sharmila, P. Subbulakshmi, ``Texture image classification and retrieval using multi-resolution radial gradient binary pattern. ``Applied Artificial Intelligence, vol. 35, no. 15, pp. 2298-2326. 2021.DOI
28 
W. Li, J. Chen, Z. Wang, Z. Shen, C. Ma, X. Cui, ``Ifl-gan: Improved federated learning generative adversarial network with maximum mean discrepancy model aggregation.'' IEEE Transactions on Neural Networks and Learning Systems. vol. 1, no. 1, pp. 1-12022.DOI