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Conf. Sci. Tech. Automat. Control Comput. Eng. (STA)","first-page":"40","article-title":"EEG data augmentation using Wasserstein GAN","author":"Bouallegue","year":"2020"},{"key":"ref2","doi-asserted-by":"crossref","DOI":"10.1016\/j.eswa.2023.120943","article-title":"WGAN-CL: A Wasserstein GAN with confidence loss for small-sample augmentation","volume":"233","author":"Mi","year":"2023, Art. no. 120943","journal-title":"Expert. Syst. Appl."},{"key":"ref3","first-page":"1","article-title":"Understanding GANs: Fundamentals, variants, training challenges, applications, and open problems","volume":"5","author":"Ahmad","year":"2024","journal-title":"Multimed. Tools Appl."},{"key":"ref4","doi-asserted-by":"crossref","first-page":"1","DOI":"10.54105\/ijipr.A8041.04030424","article-title":"An overview of text to visual generation using GAN","volume":"4","author":"Mathew","year":"2024","journal-title":"Indian J. Image Process. Recognit."},{"key":"ref5","doi-asserted-by":"crossref","DOI":"10.1002\/wics.1629","article-title":"A comprehensive review of generative adversarial networks: Fundamentals, applications, and challenges","volume":"16","author":"Megahed","year":"2024, Art. no. 1629","journal-title":"WIREs Comput. Stat."},{"key":"ref6","unstructured":"L. Weng, \u201cFrom GAN to WGAN,\u201d 2019. doi: 10.48550\/arXiv.1904.08994."},{"key":"ref7","author":"Manaswi","year":"2020","journal-title":"Generative Adversarial Networks with Industrial Use Cases: Learning How to Build GAN Applications for Retail, Healthcare, Telecom, Media, Education, and HRTech"},{"key":"ref8","doi-asserted-by":"crossref","first-page":"305","DOI":"10.1016\/S0921-5107(98)00523-6","article-title":"GAN: From fundamentals to applications","volume":"61","author":"Pankove","year":"1999","journal-title":"Mater. Sci. Eng.: B"},{"key":"ref9","first-page":"8680","article-title":"Dynamically grown generative adversarial networks","volume":"35","author":"Liu","year":"2021","journal-title":"Proc. AAAI Conf. Artif. Intell."},{"key":"ref10","doi-asserted-by":"crossref","first-page":"591","DOI":"10.1111\/cgf.14503","article-title":"State-of-the-art in the architecture, methods and applications of StyleGAN","volume":"41","author":"Bermano","year":"2022","journal-title":"Comput. Graph. Forum"},{"key":"ref11","first-page":"852","article-title":"Alias-free generative adversarial networks","volume":"34","author":"Karras","year":"2023","journal-title":"Adv. Neural Inf. Process. Syst."},{"key":"ref12","series-title":"Int. Conf. Mach. Learn.","first-page":"7354","article-title":"Self-attention generative adversarial networks","author":"Zhang","year":"2019"},{"key":"ref13","series-title":"Proc. Asian Conf. Comput. Vis.","article-title":"TinyGAN: Distilling BigGAN for conditional image generation","author":"Chang","year":"2020"},{"key":"ref14","doi-asserted-by":"crossref","first-page":"69","DOI":"10.1016\/j.neunet.2020.10.004","article-title":"CEGAN: Classification enhancement generative adversarial networks for unraveling data imbalance problems","volume":"133","author":"Suh","year":"2021","journal-title":"Neural Netw."},{"key":"ref15","first-page":"1105","article-title":"SSD-GAN: Measuring the realness in the spatial and spectral domains","volume":"35","author":"Chen","year":"2021","journal-title":"Proc. AAAI Conf. Artif. Intell."},{"key":"ref16","doi-asserted-by":"crossref","first-page":"519","DOI":"10.1109\/TMM.2021.3054509","article-title":"MIEGAN: Mobile image enhancement via a multi-module cascade neural network","volume":"24","author":"Pan","year":"2024","journal-title":"IEEE Trans. Multimed."},{"key":"ref17","unstructured":"Y. LeCun, C. Cortes, and C. J. C. Burges, \u201cDataset named \u2018mnist\u2019 dataset from Kaggle,\u201d Accessed: Sep. 20, 2024. [Online]. Available: https:\/\/www.kaggle.com\/datasets\/hojjatk\/mnist-dataset"},{"key":"ref18","unstructured":"A. Krizhevsky, V. Nair, and G. Hinton, \u201cDataset named \u2018cifar100\u2019 dataset from Kagglehttps,\u201d 2009. Accessed: Sep. 20, 2024. [Online]. Available: https:\/\/www.kaggle.com\/datasets\/fedesoriano\/cifar100"},{"key":"ref19","unstructured":"S. Yang, P. Luo, C. C. Loy, and X. Tang, \u201cDataset named \u2018celeba\u2019 dataset from Kaggle,\u201d 2015. Accessed: Sep. 20, 2024. [Online]. Available: https:\/\/www.kaggle.com\/datasets\/jessicali9530\/celeba-dataset"},{"key":"ref20","unstructured":"H. Xiao, K. Rasul, and R. Vollgraf, \u201cDataset named \u2018fashion mnist\u2019 dataset from Kaggle,\u201d 2017. Accessed: Sep. 20, 2024. [Online]. Available: https:\/\/www.kaggle.com\/datasets\/zalando-research\/fashionmnist"},{"key":"ref21","first-page":"1","article-title":"Music source separation via hybrid waveform and spectrogram based generative adversarial network","author":"Wu","year":"2024","journal-title":"Multimed. Tools Appl."},{"key":"ref22","doi-asserted-by":"crossref","first-page":"7833","DOI":"10.1007\/s11760-024-03432-6","article-title":"RSC-WSRGAN super-resolution reconstruction based on improved generative adversarial network","volume":"18","author":"Tao","year":"2024","journal-title":"Signal, Image Video Process."},{"key":"ref23","doi-asserted-by":"crossref","first-page":"14375","DOI":"10.1038\/s41598-024-65270-3","article-title":"Nighttime road scene image enhancement based on cycle-consistent generative adversarial network","volume":"14","author":"Jia","year":"2024","journal-title":"Sci. Rep."},{"key":"ref24","doi-asserted-by":"crossref","first-page":"661","DOI":"10.1007\/s10548-023-00986-5","article-title":"Generative adversarial network (GAN) for simulating electroencephalography","volume":"36","author":"Mahey","year":"2023","journal-title":"Brain Topogr."},{"key":"ref25","doi-asserted-by":"crossref","first-page":"36","DOI":"10.1007\/s11063-024-11457-8","article-title":"Information-minimizing generative adversarial network for fair generation and classification","volume":"56","author":"Chen","year":"2024","journal-title":"Neural Process. Lett."},{"key":"ref26","doi-asserted-by":"crossref","first-page":"4319","DOI":"10.1007\/s10489-024-05406-0","article-title":"Generative adversarial network for newborn 3D skeleton part segmentation","volume":"54","author":"Nguyen-Le","year":"2024","journal-title":"Appl. Intell."},{"key":"ref27","doi-asserted-by":"crossref","first-page":"5135","DOI":"10.1007\/s10994-023-06367-0","article-title":"Robust generative adversarial network","volume":"112","author":"Zhang","year":"2023","journal-title":"Mach. Learn."},{"key":"ref28","doi-asserted-by":"crossref","first-page":"65","DOI":"10.1007\/s11554-024-01446-4","article-title":"GAN-STD: Small target detection based on generative adversarial network","volume":"21","author":"Wang","year":"2024","journal-title":"J. Real Time Image Process."},{"key":"ref29","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1007\/s12145-024-01381-9","article-title":"From land to ocean: Bathymetric terrain reconstruction via conditional generative adversarial network","volume":"17","author":"Zhang","year":"2024","journal-title":"Earth Sci. Inform."},{"key":"ref30","first-page":"1","article-title":"MTUNet++: Explainable few-shot medical image classification with generative adversarial network","author":"Titoriya","year":"2024","journal-title":"Multimed. Tools Appl."},{"key":"ref31","doi-asserted-by":"crossref","first-page":"530","DOI":"10.1007\/s00339-024-07694-2","article-title":"Freeform metasurface design with a conditional generative adversarial network","volume":"130","author":"Xu","year":"2024","journal-title":"Appl. Phys. A"},{"key":"ref32","first-page":"1","article-title":"Infrared single pixel imaging based on generative adversarial network","volume":"55","author":"Jiang","year":"2023","journal-title":"J. Shanghai Jiaotong Univ. (Sci.)"},{"key":"ref33","doi-asserted-by":"crossref","first-page":"1331","DOI":"10.1007\/s13042-023-01970-y","article-title":"Underwater image enhancement based on multiscale fusion generative adversarial network","volume":"15","author":"Dai","year":"2024","journal-title":"Int. J. Mach. Learn. Cybern."},{"key":"ref34","doi-asserted-by":"crossref","first-page":"19636","DOI":"10.1038\/s41598-024-70619-9","article-title":"A novel image semantic communication method via dynamic decision generation network and generative adversarial network","volume":"14","author":"Liu","year":"2024","journal-title":"Sci. Rep."},{"key":"ref35","doi-asserted-by":"crossref","first-page":"563","DOI":"10.1134\/S1063779624030596","article-title":"Generative adversarial networks quantization","volume":"55","author":"Mitrofanov","year":"2024","journal-title":"Phys. Part. Nucl."},{"key":"ref36","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1007\/s11227-024-06198-3","article-title":"Smart GAN: A smart generative adversarial network for limited imbalanced dataset","volume":"80","author":"Kumari","year":"2024","journal-title":"J. Supercomput."},{"key":"ref37","first-page":"1","article-title":"PMGAN: Pretrained model-based generative adversarial network for text-to-image generation","volume":"34","author":"Yu","year":"2024","journal-title":"Vis. Comput."},{"key":"ref38","doi-asserted-by":"crossref","first-page":"7621","DOI":"10.1007\/s11760-024-03415-7","article-title":"Image inpainting based on tensor ring decomposition with generative adversarial network","volume":"18","author":"Yuan","year":"2024","journal-title":"Signal, Image Video Process."},{"key":"ref39","doi-asserted-by":"crossref","first-page":"93","DOI":"10.1007\/s10922-024-09867-z","article-title":"Generative adversarial network models for anomaly detection in software-defined networks","volume":"32","author":"Zacaron","year":"2024","journal-title":"J. Network Syst. Manag."},{"key":"ref40","doi-asserted-by":"crossref","first-page":"3725","DOI":"10.1007\/s00500-024-09636-9","article-title":"Fault identification of product design using fuzzy clustering generative adversarial network (FCGAN) model","volume":"28","author":"Wang","year":"2024","journal-title":"Soft Comput."},{"key":"ref41","doi-asserted-by":"crossref","first-page":"541","DOI":"10.1007\/s12206-024-0104-2","article-title":"Imbalanced data fault diagnosis of rolling bearings using enhanced relative generative adversarial network","volume":"38","author":"Luo","year":"2024","journal-title":"J. Mech. Sci. Technol."},{"key":"ref42","doi-asserted-by":"crossref","first-page":"12382","DOI":"10.1038\/s41598-024-63259-6","article-title":"Remote sensing image dehazing using generative adversarial network with texture and color space enhancement","volume":"14","author":"Shen","year":"2024","journal-title":"Sci. Rep."},{"key":"ref43","doi-asserted-by":"crossref","first-page":"5079","DOI":"10.1007\/s10792-023-02911-y","article-title":"A generative adversarial neural network with multi-attention feature extraction for fundus lesion segmentation","volume":"43","author":"Yuan","year":"2024","journal-title":"Int. Ophthalmol."},{"key":"ref44","doi-asserted-by":"crossref","first-page":"288","DOI":"10.1007\/s42979-024-02610-0","article-title":"Efficient segmentation of vessels and disc simultaneously using multi-channel generative adversarial network","volume":"5","author":"Kar","year":"2024","journal-title":"SN Comput. Sci."},{"key":"ref45","first-page":"1","article-title":"Brain magnetic resonance image inpainting via deep edge region-based generative adversarial network","author":"Kala","year":"2024","journal-title":"J. Electr. Eng. Technol."},{"key":"ref46","doi-asserted-by":"crossref","first-page":"1076","DOI":"10.1109\/TAI.2022.3196283","article-title":"Evasion generative adversarial network for low data regimes","volume":"4","author":"Randhawa","year":"Oct. 2023","journal-title":"IEEE Trans. Artif. Intell."},{"key":"ref47","first-page":"1","article-title":"SAR image ship object generation and classification with improved residual conditional generative adversarial network","volume":"19","author":"Li","year":"2022, Art. no. 4000105","journal-title":"IEEE Geosci. Remote Sens. Lett."},{"key":"ref48","doi-asserted-by":"crossref","first-page":"480","DOI":"10.1109\/TCCN.2022.3153004","article-title":"Machine learning in NextG networks via generative adversarial networks","volume":"8","author":"Ayanoglu","year":"Jun. 2022","journal-title":"IEEE Trans. Cogn. Commun. Netw."},{"key":"ref49","doi-asserted-by":"crossref","first-page":"1114","DOI":"10.1109\/LSP.2024.3386491","article-title":"Jamming waveform generation method based on generative adversarial network model","volume":"31","author":"Jiang","year":"2024","journal-title":"IEEE Signal Process. Lett."},{"key":"ref50","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1109\/LGRS.2020.3041864","article-title":"Mixture of spectral generative adversarial networks for imbalanced hyperspectral image classification","volume":"19","author":"Dam","year":"2022","journal-title":"IEEE Geosci. Remote Sens. Lett."},{"key":"ref51","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1109\/TGRS.2023.3335484","article-title":"AVO inversion based on closed-loop multitask conditional wasserstein generative adversarial network","volume":"61","author":"Wang","year":"2023","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref52","doi-asserted-by":"crossref","first-page":"319","DOI":"10.23919\/comex.2024XBL0062","article-title":"Proposal of temporal feature layers for network traffic dataset generation using C-GAN","volume":"13","author":"Onodera","year":"Aug. 2024","journal-title":"IEICE Commun. Express"},{"key":"ref53","doi-asserted-by":"crossref","first-page":"29","DOI":"10.1109\/LMWT.2023.3329047","article-title":"Inverse design of dual-band microstrip filters based on generative adversarial network","volume":"34","author":"Zhang","year":"Jan. 2024","journal-title":"IEEE Microw. Wirel. Technol. Lett."},{"key":"ref54","first-page":"2594","article-title":"Inverse design of tunable lowpass microstrip filters based on generative adversarial network and transfer learning","volume":"71","author":"Zhang","year":"May 2024","journal-title":"IEEE Trans. Circuits Syst. II"},{"key":"ref55","doi-asserted-by":"crossref","first-page":"1810","DOI":"10.1109\/LED.2022.3207784","article-title":"Out-of-training-range synthetic FinFET and inverter data generation using a modified generative adversarial network","volume":"43","author":"Eranki","year":"Nov. 2022","journal-title":"IEEE Electron Device Lett."},{"key":"ref56","doi-asserted-by":"crossref","first-page":"1988","DOI":"10.1109\/LSP.2022.3207621","article-title":"Laplacian pyramid generative adversarial network for infrared and visible image fusion","volume":"29","author":"Yin","year":"2022","journal-title":"IEEE Signal Process. Lett."},{"key":"ref57","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1109\/TMAG.2022.3171350","article-title":"Discovering pareto-optimal magnetic-design solutions via a generative adversarial network","volume":"58","author":"Baldan","year":"Sep. 2022","journal-title":"IEEE Trans. Magn."},{"key":"ref58","first-page":"1","article-title":"Generative adversarial network with transformer for hyperspectral image classification","volume":"20","author":"Hao","year":"2023","journal-title":"IEEE Geosci. Remote Sens. Lett."},{"key":"ref59","doi-asserted-by":"crossref","first-page":"88152","DOI":"10.1109\/ACCESS.2023.3305994","article-title":"Generating chest X-ray progression of pneumonia using conditional cycle generative adversarial networks","volume":"11","author":"Jin","year":"2023","journal-title":"IEEE Access"},{"key":"ref60","doi-asserted-by":"crossref","first-page":"9733","DOI":"10.1109\/TPAMI.2021.3127346","article-title":"ZeroNAS: Differentiable generative adversarial networks search for zero shot learning","volume":"44","author":"Yan","year":"Dec. 1, 2022","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell."},{"key":"ref61","first-page":"1","article-title":"DeepDT: Generative adversarial network for high-resolution climate prediction","volume":"19","author":"Cheng","year":"2022","journal-title":"IEEE Geosci. Remote Sens. Lett."},{"key":"ref62","first-page":"1","article-title":"Balancing colors of nonoverlapping mosaicking images with generative adversarial networks","volume":"19","author":"Ma","year":"2022","journal-title":"IEEE Geosci. Remote Sens. Lett."},{"key":"ref63","doi-asserted-by":"crossref","first-page":"17646","DOI":"10.1109\/JSEN.2021.3066200","article-title":"Robotic musicianship based on least squares and sequence generative adversarial networks","volume":"22","author":"Chen","year":"Sep. 15, 2022","journal-title":"IEEE Sens. J."},{"key":"ref64","doi-asserted-by":"crossref","first-page":"582","DOI":"10.1109\/TEVC.2023.3307245","article-title":"EGANS: Evolutionary generative adversarial network search for zero shot learning","volume":"28","author":"Chen","year":"Jun. 2024","journal-title":"IEEE Trans. Evol. Comput."},{"key":"ref65","doi-asserted-by":"crossref","first-page":"2330","DOI":"10.1109\/JIOT.2022.3211346","article-title":"An enhanced AI-based network intrusion detection system using generative adversarial networks","volume":"10","author":"Park","year":"Feb. 1, 2023","journal-title":"IEEE Internet Things J."},{"key":"ref66","doi-asserted-by":"crossref","first-page":"5144","DOI":"10.1109\/ACCESS.2023.3236575","article-title":"Feature interpretation using generative adversarial networks (FIGAN): A framework for visualizing a CNN\u2019s learned features","volume":"11","author":"Hasenstab","year":"2023","journal-title":"IEEE Access"},{"key":"ref67","first-page":"1","article-title":"The application of semisupervised attentional generative adversarial networks in desert seismic data denoising","volume":"19","author":"Li","year":"2022","journal-title":"IEEE Geosci. Remote Sens. Lett."},{"key":"ref68","doi-asserted-by":"crossref","first-page":"105022","DOI":"10.1109\/ACCESS.2022.3211394","article-title":"Ganster R-CNN: Occluded object detection network based on generative adversarial nets and faster R-CNN","volume":"10","author":"Sun","year":"2022","journal-title":"IEEE Access"},{"key":"ref69","doi-asserted-by":"crossref","first-page":"70690","DOI":"10.1109\/ACCESS.2024.3402069","article-title":"An unsupervised generative adversarial network system to Detect DDoS attacks in SDN","volume":"12","author":"Brand\u00e3o Lent","year":"2024","journal-title":"IEEE Access"},{"key":"ref70","first-page":"1","article-title":"Improved generative adversarial networks for VHR remote sensing image classification","volume":"19","author":"Shi","year":"2022","journal-title":"IEEE Geosci. Remote Sens. Lett."},{"key":"ref71","first-page":"1","article-title":"Selecting information fusion generative adversarial network for remote sensing image cloud removal","volume":"20","author":"Hao","year":"2023, Art. no. 6007605","journal-title":"IEEE Geosci. Remote Sens. Lett."},{"key":"ref72","doi-asserted-by":"crossref","first-page":"107416","DOI":"10.1109\/ACCESS.2022.3212751","article-title":"A network security situation element extraction method based on conditional generative adversarial network and transformer","volume":"10","author":"Yang","year":"2022","journal-title":"IEEE Access"},{"key":"ref73","doi-asserted-by":"crossref","first-page":"706","DOI":"10.1109\/LSP.2024.3365034","article-title":"Active defense against voice conversion through generative adversarial network","volume":"31","author":"Dong","year":"2024","journal-title":"IEEE Signal Process. Lett."},{"key":"ref74","doi-asserted-by":"crossref","first-page":"3538","DOI":"10.1109\/TNNLS.2021.3111911","article-title":"An intelligent method for predicting the pressure coefficient curve of airfoil-based conditional generative adversarial networks","volume":"34","author":"Wang","year":"Jul. 2023","journal-title":"IEEE Trans. Neural Netw. Learn. Syst."},{"key":"ref75","first-page":"1","article-title":"Deep convolutional generative adversarial network with autoencoder for semisupervised SAR image classification","volume":"19","author":"Zhang","year":"2022, Art. no. 4000405","journal-title":"IEEE Geosci. Remote Sens. Lett."},{"key":"ref76","doi-asserted-by":"crossref","first-page":"1504","DOI":"10.1109\/JBHI.2023.3340325","article-title":"Graph-based conditional generative adversarial networks for major depressive disorder diagnosis with synthetic functional brain network generation","volume":"28","author":"Oh","year":"Mar. 2024","journal-title":"IEEE J. Biomed. Health Inform."},{"key":"ref77","doi-asserted-by":"crossref","first-page":"3473","DOI":"10.1109\/TNNLS.2021.3116419","article-title":"Attribute augmented network embedding based on generative adversarial nets","volume":"34","author":"Zheng","year":"Jul. 2023","journal-title":"IEEE Trans. Neural Netw. Learn. Syst."},{"key":"ref78","doi-asserted-by":"crossref","first-page":"355","DOI":"10.1109\/LCOMM.2021.3131476","article-title":"UniQGAN: Unified generative adversarial networks for augmented modulation classification","volume":"26","author":"Lee","year":"Feb. 2022","journal-title":"IEEE Commun. Lett."},{"key":"ref79","doi-asserted-by":"crossref","first-page":"5684","DOI":"10.1109\/TNNLS.2022.3208914","article-title":"WalkGAN: Network representation learning with sequence-based generative adversarial networks","volume":"35","author":"Jin","year":"Apr. 2024","journal-title":"IEEE Trans. Neural Netw. Learn. Syst."},{"key":"ref80","doi-asserted-by":"crossref","first-page":"33602","DOI":"10.1109\/ACCESS.2022.3160283","article-title":"ARGAN: Adversarially robust generative adversarial networks for deep neural networks against adversarial examples","volume":"10","author":"Choi","year":"2022","journal-title":"IEEE Access"}],"container-title":["Computers, Materials & Continua"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/cdn.techscience.cn\/files\/cmc\/2025\/TSP_CMC-82-2\/TSP_CMC_59715\/TSP_CMC_59715.pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,11,14]],"date-time":"2025-11-14T06:12:41Z","timestamp":1763100761000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.techscience.com\/cmc\/v82n2\/59505"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025]]},"references-count":80,"journal-issue":{"issue":"2","published-online":{"date-parts":[[2025]]},"published-print":{"date-parts":[[2025]]}},"URL":"https:\/\/doi.org\/10.32604\/cmc.2024.059715","relation":{},"ISSN":["1546-2226"],"issn-type":[{"value":"1546-2226","type":"electronic"}],"subject":[],"published":{"date-parts":[[2025]]},"assertion":[{"value":"2024-10-15","order":0,"name":"received","label":"Received","group":{"name":"publication_history","label":"Publication History"}},{"value":"2024-12-12","order":1,"name":"accepted","label":"Accepted","group":{"name":"publication_history","label":"Publication History"}},{"value":"2025-02-17","order":2,"name":"published","label":"Published Online","group":{"name":"publication_history","label":"Publication History"}}]}}