INFORMAZIONI SU QUESTO ARTICOLO

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Murshed H,Wei Z,Ahmed M . Perfect Single Image (SR)Super-Resolutionwith,Deep Super Resolution Convolutional Neural NetworkandOpenCV Method [J]. IOSR journal of computer engineering, 2020(3):22. Murshed H Wei Z Ahmed M. Perfect Single Image (SR)Super-Resolutionwith,Deep Super Resolution Convolutional Neural NetworkandOpenCV Method [J]. IOSR journal of computer engineering , 2020 ( 3 ): 22 . Search in Google Scholar

Ward C M, Harguess J, Crabb. Image quality assessment for determining efficacy and limitations of Super-Resolution Convolutional Neural Network (SRCNN)[C]//Applications of Digital Image Processing XL. SPIE, 2017, 10396: 19-30. Ward C M Harguess J Crabb Image quality assessment for determining efficacy and limitations of Super-Resolution Convolutional Neural Network (SRCNN) [C]// Applications of Digital Image Processing XL. SPIE , 2017 , 10396 : 19 30 . Search in Google Scholar

Wang Lie, Yin Jin-wei. Small Object Detection Method Based on SRCNN and SSD network [J].Computer simulation, 2020, 37(3):5. Wang Lie Yin Jin-wei Small Object Detection Method Based on SRCNN and SSD network [J] . Computer simulation , 2020 , 37 ( 3 ): 5 . Search in Google Scholar

Shen H F, Li P X, Zhang L P. Overview of image super-resolution reconstruction techniques and methods [J]. Optical Technology, 2009(2):7. Shen H F Li P X Zhang L P. Overview of image super-resolution reconstruction techniques and methods [J]. Optical Technology , 2009 ( 2 ): 7 . Search in Google Scholar

Pu Jian, Zhang Junping, Huang Hua. Review of super-resolution algorithms [J]. Journal of Shandong University: Engineering Science Edition, 2009(1):6. Pu Jian Zhang Junping Huang Hua Review of super-resolution algorithms [J]. Journal of Shandong University: Engineering Science Edition , 2009 ( 1 ): 6 . Search in Google Scholar

ANWARS, KHANS, BARNESN. A deep journey into super-resolution: a survey[J]. ACM Computing Surveys (CSUR), 2020, 53(3):1–34. Anwars Khans Barnesn A deep journey into super-resolution: a survey [J]. ACM Computing Surveys (CSUR) , 2020 , 53 ( 3 ): 1 34 . Search in Google Scholar

Kim J, Lee J K, Lee K M. Accurate Image Super-Resolution Using Very Deep Convolutional Networks[C]// IEEE Conference on Computer Vision & Pattern Recognition. IEEE, 2016 Kim J Lee J K Lee K M. Accurate Image Super-Resolution Using Very Deep Convolutional Networks [C]// IEEE Conference on Computer Vision & Pattern Recognition . IEEE , 2016 Search in Google Scholar

Wang Jiaming, LU Tao. Satellite image super-resolution algorithm based on multi-scale residual deep neural network [J]. Journal of Wuhan Institute of Technology, 2018, 40(04):440–445. Wang Jiaming LU Tao Satellite image super-resolution algorithm based on multi-scale residual deep neural network [J]. Journal of Wuhan Institute of Technology , 2018 , 40 ( 04 ): 440 445 . Search in Google Scholar

Wan Xuefen, Cui Jian, WANG Guanjun. Research on Image Super-resolution Reconstruction Processing Algorithm[C]// National Conference on Optoelectronics and Quantum Electronics Technology. Chinese Institute of Electronics, 2011. Wan Xuefen Cui Jian WANG Guanjun . Research on Image Super-resolution Reconstruction Processing Algorithm [C]// National Conference on Optoelectronics and Quantum Electronics Technology . Chinese Institute of Electronics , 2011 . Search in Google Scholar

TIAN Yan, TIAN Jinwen, LIU Jian. Implementation for Super Resolution--An Improved Image Interpolation Based on Wavelet Implementation of Super-Resolution Technology -- An Improved Wavelet Interpolation Method [J]. Journal of Image and Graphics, 2003, 45(12):1422–1426. TIAN Yan TIAN Jinwen LIU Jian Implementation for Super Resolution--An Improved Image Interpolation Based on Wavelet Implementation of Super-Resolution Technology -- An Improved Wavelet Interpolation Method [J]. Journal of Image and Graphics , 2003 , 45 ( 12 ): 1422 1426 . Search in Google Scholar

Jiang Hao, Wang Bofu, Zhuang Qiliang. Reconstruction of turbulent flow field based on super-resolution reconstruction method [J]. Experimental Fluid Mechanics, 2022(036-003). Jiang Hao Wang Bofu Zhuang Qiliang Reconstruction of turbulent flow field based on super-resolution reconstruction method [J]. Experimental Fluid Mechanics , 2022 ( 036-003 ). Search in Google Scholar

Wang Rong, Zhang Yonghui, Zhang Jian. Image supe-resolution Reconstruction Method based on CNN [J]. Computer Engineering and Design, 2019, 40(6):6. Wang Rong Zhang Yonghui Zhang Jian Image super-resolution Reconstruction Method based on CNN [J]. Computer Engineering and Design , 2019 , 40 ( 6 ): 6 . Search in Google Scholar

Zhong Z, Chen Y, Hou S. Super-resolution reconstruction method of infrared images of composite insulators with abnormal heating based on improved SRGAN [J]. IET generation, transmission & distribution, 2022(10):16. Zhong Z Chen Y Hou S. Super-resolution reconstruction method of infrared images of composite insulators with abnormal heating based on improved SRGAN [J]. IET generation, transmission & distribution , 2022 ( 10 ): 16 Search in Google Scholar

Zou Penghui, Zeng Yijie, Duan Zhenghong. Research on image super-resolution Reconstruction based on SRGAN technology [J]. Science and Technology Trends, 2019(18):1. Zou Penghui Zeng Yijie Duan Zhenghong Research on image super-resolution Reconstruction based on SRGAN technology [J]. Science and Technology Trends , 2019 ( 18 ): 1 . Search in Google Scholar

Liu Yiwen. Research on Low resolution face Detection Algorithm Based on Deep Learning [D]. University of Electronic Science and Technology of China, 2019. Liu Yiwen Research on Low resolution face Detection Algorithm Based on Deep Learning [D] . University of Electronic Science and Technology of China , 2019 . Search in Google Scholar

Hu Lei, Wang Zugen, Chen Tian, et al. An Improved super-resolution Reconstruction algorithm for SRGAN infrared Image [J]. Journal of System Simulation, 2021(033-009). Hu Lei Wang Zugen Chen Tian An Improved super-resolution Reconstruction algorithm for SRGAN infrared Image [J]. Journal of System Simulation , 2021 ( 033-009 ). Search in Google Scholar

Nagano Y, Kikuta Y. SRGAN for super-resolving low-resolution food images[C]//Proceedings of the Joint Workshop on Multimedia for Cooking and Eating Activities and Multimedia Assisted Dietary Management. 2018: 33-37. Nagano Y Kikuta Y. SRGAN for super-resolving low-resolution food images [C]// Proceedings of the Joint Workshop on Multimedia for Cooking and Eating Activities and Multimedia Assisted Dietary Management . 2018 : 33 37 . Search in Google Scholar

Li J, Wu L, Wang S. Super resolution image reconstruction of textile based on SRGAN[C]//2019 IEEE International Conference on Smart Internet of Things (SmartIoT). IEEE, 2019: 436-439. Li J Wu L Wang S. Super resolution image reconstruction of textile based on SRGAN [C]// 2019 IEEE International Conference on Smart Internet of Things (SmartIoT) . IEEE , 2019 : 436 439 . Search in Google Scholar

Wang X, Yu K, Wu S. Esrgan: Enhanced super-resolution generative adversarial networks[C]//Proceedings of the European conference on computer vision (ECCV) workshops. 2018: 0-0. Wang X Yu K Wu S. Esrgan: Enhanced super-resolution generative adversarial networks [C]// Proceedings of the European conference on computer vision (ECCV) workshops . 2018 : 0 0 . Search in Google Scholar

Wang X, Xie L, Dong C. Real-esrgan: Training real-world blind super-resolution with pure synthetic data[C]//Proceedings of the IEEE/CVF International Conference on Computer Vision. 2021: 1905-1914. Wang X Xie L Dong C. Real-esrgan: Training real-world blind super-resolution with pure synthetic data [C]// Proceedings of the IEEE/CVF International Conference on Computer Vision . 2021 : 1905 1914 . Search in Google Scholar

Menon S, Damian A, Hu S. Pulse: Self-supervised photo upsampling via latent space exploration of generative models[C]//Proceedings of the ieee/cvf conference on computer vision and pattern recognition. 2020: 2437-2445. Menon S Damian A Hu S. Pulse: Self-supervised photo upsampling via latent space exploration of generative models [C]// Proceedings of the ieee/cvf conference on computer vision and pattern recognition . 2020 : 2437 2445 . Search in Google Scholar

eISSN:
2470-8038
Lingua:
Inglese
Frequenza di pubblicazione:
4 volte all'anno
Argomenti della rivista:
Computer Sciences, other