Aslan M, Baykara M, Alakuş TB (2024) Analysis of brain areas in emotion recognition from eeg signals with deep learning methods. Multimed Tools Appl 83(11):32423–32452. https://doi.org/10.1007/s11042-023-16696-w
Aydin S, Onbaşi L (2024) Graph theoretical brain connectivity measures to investigate neural correlates of music rhythms associated with fear and anger. Cogn Neurodyn 18:49–66. https://doi.org/10.1007/s11571-023-09931-5
Basheer S, Aldehim G, Alluhaidan AS, Sakri S (2024) Improving mental dysfunction detection from EEG signals: self-contrastive learning and multitask learning with transformers. Alexandria Eng J 106:52–59. https://doi.org/10.1016/j.aej.2024.06.058
Brockschmidt M (2020) GNN-FiLM: graph neural networks with feature-wise linear modulation. In: International conference on machine learning, pp. 1144–1152
Chen J, Wang X, Huang C, Hu X, Shen X, Zhang D (2023b) A large finer-grained affective computing EEG dataset. Sci Data 10(1):740. https://doi.org/10.1038/s41597-023-02650-w
Article PubMed PubMed Central Google Scholar
Chen J, Kao SH, He H, Zhuo W, Wen S, Lee CH, Chan SHG (2023) Run, don’t walk: chasing higher FLOPS for faster neural networks. In: Proceedings of the IEEE/CVF conference on computer vision and pattern recognition, Vancouver, Canada, 2023, pp. 12021–12031
Cheng C, Yu Z, Zhang Y, Feng L (2023) Hybrid network using dynamic graph convolution and temporal self-attention for EEG-based emotion recognition. IEEE Trans Neural Networks Learn Syst. https://doi.org/10.1109/TNNLS.2023.3319315
Dempster A, Petitjean F, Webb GI (2020) ROCKET: exceptionally fast and accurate time series classification using random convolutional kernels. Data Min Knowl Discov 34(5):1454–1495. https://doi.org/10.1007/s10618-020-00701-z
Du Y, Ding H, Wu M, Chen F, Cai Z (2024) MES-CTNet: a novel capsule transformer network base on a multi-domain feature map for electroencephalogram-based emotion recognition. Brain Sci 14(4):344. https://doi.org/10.3390/brainsci14040344
Article PubMed PubMed Central Google Scholar
Eisenhauer S, Gonzalez Alam TR, Cornelissen PL, Smallwood J, Jefferies E (2024) Individual word representations dissociate from linguistic context along a cortical unimodal to heteromodal gradient. Hum Brain Mapping. 45(2):e26607. https://doi.org/10.1002/hbm.26607
Eldele E, Ragab M, Chen Z, Wu M, Li X (2024) Tslanet: rethinking transformers for time series representation learning. In: Proceedings of the 41st international conference on machine learning, Vienna, Austria, pp. 1–6
Ferreira ADM, Willmersdorf RB, Afonso SM (2024) Corroded pipeline assessment using neural networks, the finite element method and discrete wavelet transforms. Adv Eng Softw 196:103721. https://doi.org/10.1016/j.advengsoft.2024.103721
Gao H, Wang X, Chen Z, Wu M, Cai Z, Zhao L, Li J, Liu C (2024a) Graph convolutional network with connectivity uncertainty for EEG-based emotion recognition. IEEE J Biomed Health Inf. https://doi.org/10.1109/JBHI.2024.3416944
Gao Y, Zhu Z, Fang F, Zhang Y, Meng M (2024b) EEG emotion recognition based on data-driven signal auto-segmentation and feature fusion. J Affect Disord 361:356–366. https://doi.org/10.1016/j.jad.2024.06.042
Handa P, Gupta M, Gupta E, Goel N (2024) One-dimensional atrous conv-net based architecture for automatic diagnosis of epilepsy using electroencephalography signals and its brain–computer interface applications. Expert Syst 41(4):e13514. https://doi.org/10.1111/exsy.13514
Hou Z, Yu B, Wang C, Zhan Y, Tao D (2022) Batchformerv2: Exploring sample relationships for dense representation learning, arXiv preprint arXiv:2204.01254. https://doi.org/10.48550/arXiv.2204.01254
Huang G, Wang Y, Lv K, Jiang H, Huang W, Qi P, Song S (2022) Glance and focus networks for dynamic visual recognition. IEEE Trans Pattern Anal Mach Intell 45(4):4605–4621. https://doi.org/10.1109/TPAMI.2022.3196959
Jastrzebski S, Kenton Z, Arpit D, Ballas N, Fischer A, Bengio Y, Storkey A (2017) Three factors influencing minima in sgd, 2017, arXiv preprint arXiv:1711.04623. https://doi.org/10.48550/arXiv.1711.04623
Kiliç B, Aydin S (2022) Classification of contrasting discrete emotional states indicated by EEG based graph theoretical network measures. Neuroinform 20:863–877. https://doi.org/10.1007/s12021-022-09579-2
King M, Woo SI, Yune CY (2024) Utilizing a CNN-RNN machine learning approach for forecasting time-series outlet fluid temperature monitoring by long-term operation of BHEs system. Geothermics 122:103082
Kumar DK, Nataraj JL (2019) Analysis of EEG based emotion detection of DEAP and SEED-IV databases using SVM. Int J Recent Technol Eng 8(1c):207–211. https://doi.org/10.2139/ssrn.3509130
Li W, Huan W, Shao S, Hou B, Song A (2023) MS-FRAN: a novel multi-source domain adaptation method for EEG-based emotion recognition. IEEE J Biomed Health Inf 27(11):5302–5313. https://doi.org/10.1109/JBHI.2023.3311338
Li G, Ao J, Hu J, Hu D, Liu Y, Huang Z (2024) Dual-source gramian angular field method and its application on fault diagnosis of drilling pump fluid end. Expert Syst Appl 237:121521. https://doi.org/10.1016/j.eswa.2023.121521
Liao J, Li H, Zhan C, Yang F (2023) Construction of an epileptic seizure prediction model using a semi-supervised method of generative adversarial and long short term memory network combined with Stockwell transform. J Southern Med Univ 43(1):17–28
Liu J, Zhang Q (2024) Multi-level modality-specific and modality-common features fusion network for RGB-IR person re-identification. Neurocomputing 600:128183. https://doi.org/10.1016/j.neucom.2024.128183
Liu R, Chao Y, Ma X, Sha X, Sun L, Li S, Chang S (2024) ERTNet: an interpretable transformer-based framework for EEG emotion recognition. Front Neurosci 18:1320645. https://doi.org/10.3389/fnins.2024.1320645
Article PubMed PubMed Central Google Scholar
Mishra R, Sharma K, Jha RR, Bhavsar A (2023) NeuroGAN: image reconstruction from EEG signals via an attention-based GAN. Neural Comput Appl 35(12):9181–9192. https://doi.org/10.1007/s00521-022-08178-1
Mutawa A, Hassouneh A (2024) Multimodal Real-Time patient emotion recognition system using facial expressions and brain EEG signals based on machine learning and log-sync methods. Biomed Signal Process Control 91:105942. https://doi.org/10.1016/j.bspc.2023.105942
Y. Nie, N.H. Nguyen, P. Sinthong, J. Kalagnanam, A time series is worth 64 words: long-term forecasting with transformers. In: The 10th international conference on learning representations, pp. 1–6.
Özçelik BY, Altan A (2023b) Overcoming nonlinear dynamics in diabetic retinopathy classification: a robust AI-based model with chaotic swarm intelligence optimization and recurrent long short-term memory. Fract Fractional 7(8):589
Özçelik BY, Altan A (2023) A comparative analysis of artificial intelligence optimization algorithms for the selection of entropy-based features in the early detection of epileptic seizures. In: The 14th international conference on electrical and electronics engineering, Bursa, Turkey, pp.1–5
Pan D, Zheng H, Xu F, Ouyang Y, Jia Z, Wang C, Zeng H (2023) MSFR-GCN: A multi-scale feature reconstruction graph convolutional network for EEG emotion and cognition recognition. IEEE Trans Neural Syst Rehabil Eng 31:3245–3254. https://doi.org/10.1109/TNSRE.2023.3304660
Park S, Yeo YJ, Shin YG (2022) PConv: simple yet effective convolutional layer for generative adversarial network. Neural Comput Appl 34(9):7113–7124. https://doi.org/10.1007/s00521-021-06846-2
Peng X, Wei Y, Deng A, Wang D, Hu D (2022) Balanced multimodal learning via on-the-fly gradient modulation, arXiv preprint arXiv:2203.15332. https://doi.org/10.48550/arXiv.2203.15332
Shi X, She Q, Fang F, Meng M, Tan T, Zhang Y (2024) Enhancing cross-subject EEG emotion recognition through multi-source manifold metric transfer learning. Comput Biol Med 174:108445. https://doi.org/10.1016/j.compbiomed.2024.108445
Singh D, Choi Y, Park J, Salman AK, Sayeed A, Song CH (2024) Deep-BCSI: a deep learning-based framework for bias correction and spatial imputation of PM2.5 concentrations in South Korea. Atmos. Res. 301:107283. https://doi.org/10.1016/j.atmosres.2024.107283
Song T, Ren Z, Zhang J, Wang M (2024) Multi-view and multimodal graph convolutional neural network for autism spectrum disorder diagnosis. Mathematics 12(11):1648. https://doi.org/10.3390/math12111648
Spivey RB, Drislane LE (2024) Meanness and affective processing: a meta-analysis of EEG findings on emotional face processing in individuals with psychopathic traits. Biol Psychol 187:108764. https://doi.org/10.1016/j.biopsycho.2024.108764
Sun J, Peng Y (2024) The cross-modality survival prediction method of glioblastoma based on dual-graph neural networks. Expert Syst Appl 254:124394. https://doi.org/10.1016/j.eswa.2024.124394
Tang H, Xie S, Xie X, Cui Y, Li B, Zheng D, Hao Y, Wang X, Jiang Y, Tian Z (2024) Multi-domain based dynamic graph representation learning for EEG emotion recognition. IEEE J Biomed Health Inf. https://doi.org/10.1109/JBHI.2024.3415163
Wang Z, Wang Y, Tang Y, Pan Z, Zhang J (2024a) Knowledge distillation based lightweight domain adversarial neural network for electroencephalogram-based emotion recognition. Biomed Signal Process Control 95:106465. https://doi.org/10.1016/j.bspc.2024.106465
Wang Y, Peng Y, Han M, Liu X, Niu H, Cheng J, Chang S, Liu T (2024b) GCTNet: a graph convolutional transformer network for major depressive disorder detection based on EEG signals. J Neural Eng 21(3):036042. https://doi.org/10.1088/1741-2552/ad5048
留言 (0)