Deep learning method for enhancing luminescence image resolution
暂无分享,去创建一个
[1] Z. Hameiri,et al. A deep learning approach to increase luminescence image resolution of solar cells , 2022, 2022 IEEE 49th Photovoltaics Specialists Conference (PVSC).
[2] Z. Hameiri,et al. A Deep Learning Approach to Denoise Electroluminescence Images of Solar Cells , 2022, 2022 IEEE 49th Photovoltaics Specialists Conference (PVSC).
[3] I. Burud,et al. Inspection and condition monitoring of large-scale photovoltaic power plants: A review of imaging technologies , 2022, Renewable and Sustainable Energy Reviews.
[4] Steven C. H. Hoi,et al. Deep Learning for Image Super-Resolution: A Survey , 2019, IEEE Transactions on Pattern Analysis and Machine Intelligence.
[5] Ian Goodfellow,et al. Generative adversarial networks , 2020, Commun. ACM.
[6] Yuki Shinomiya,et al. 3D Brain MRI Reconstruction based on 2D Super-Resolution Technology , 2020, 2020 IEEE International Conference on Systems, Man, and Cybernetics (SMC).
[7] Matthias Schubert,et al. Small-Object Detection in Remote Sensing Images with End-to-End Edge-Enhanced GAN and Object Detector Network , 2020, Remote. Sens..
[8] Yingzheng Liu,et al. Super-resolution reconstruction of turbulent velocity fields using a generative adversarial network-based artificial intelligence framework , 2019 .
[9] Violeta Holmes,et al. Solar cells micro crack detection technique using state-of-the-art electroluminescence imaging , 2019 .
[10] Radu Timofte,et al. 2018 PIRM Challenge on Perceptual Image Super-resolution , 2018, ArXiv.
[11] Yun Fu,et al. Residual Dense Network for Image Super-Resolution , 2018, 2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition.
[12] Alexei A. Efros,et al. The Unreasonable Effectiveness of Deep Features as a Perceptual Metric , 2018, 2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition.
[13] F. Creutzig,et al. The underestimated potential of solar energy to mitigate climate change , 2017, Nature Energy.
[14] Jian Yang,et al. MemNet: A Persistent Memory Network for Image Restoration , 2017, 2017 IEEE International Conference on Computer Vision (ICCV).
[15] Jian Yang,et al. Image Super-Resolution via Deep Recursive Residual Network , 2017, 2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).
[16] Bernhard Schölkopf,et al. EnhanceNet: Single Image Super-Resolution Through Automated Texture Synthesis , 2016, 2017 IEEE International Conference on Computer Vision (ICCV).
[17] Christian Ledig,et al. Photo-Realistic Single Image Super-Resolution Using a Generative Adversarial Network , 2016, 2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).
[18] Xiaoou Tang,et al. Accelerating the Super-Resolution Convolutional Neural Network , 2016, ECCV.
[19] Gregory Wilson,et al. Economically sustainable scaling of photovoltaics to meet climate targets , 2016, 2016 IEEE 43rd Photovoltaic Specialists Conference (PVSC).
[20] Martin A. Green,et al. Commercial progress and challenges for photovoltaics , 2016, Nature Energy.
[21] Kyoung Mu Lee,et al. Accurate Image Super-Resolution Using Very Deep Convolutional Networks , 2015, 2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).
[22] Kyoung Mu Lee,et al. Deeply-Recursive Convolutional Network for Image Super-Resolution , 2015, 2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).
[23] Xiaoou Tang,et al. Image Super-Resolution Using Deep Convolutional Networks , 2014, IEEE Transactions on Pattern Analysis and Machine Intelligence.
[24] Thomas B. Moeslund,et al. Super-resolution: a comprehensive survey , 2014, Machine Vision and Applications.
[25] Geoffrey E. Hinton,et al. ImageNet classification with deep convolutional neural networks , 2012, Commun. ACM.
[26] Liangpei Zhang,et al. A super-resolution reconstruction algorithm for hyperspectral images , 2012, Signal Process..
[27] Liangpei Zhang,et al. Multiframe Super-Resolution Employing a Spatially Weighted Total Variation Model , 2012, IEEE Transactions on Circuits and Systems for Video Technology.
[28] Thorsten Trupke,et al. Photoluminescence Imaging for Photovoltaic Applications , 2012 .
[29] Simon K. Warfield,et al. Robust Super-Resolution Volume Reconstruction From Slice Acquisitions: Application to Fetal Brain MRI , 2010, IEEE Transactions on Medical Imaging.
[30] Kwang In Kim,et al. Single-Image Super-Resolution Using Sparse Regression and Natural Image Prior , 2010, IEEE Transactions on Pattern Analysis and Machine Intelligence.
[31] Michal Irani,et al. Super-resolution from a single image , 2009, 2009 IEEE 12th International Conference on Computer Vision.
[32] Vorapoj Patanavijit,et al. Super-Resolution Reconstruction and Its Future Research Direction , 2009 .
[33] Yi Wang,et al. Super-resolution mosaicking of UAV surveillance video , 2008, 2008 15th IEEE International Conference on Image Processing.
[34] H. Shum,et al. Image super-resolution using gradient profile prior , 2008, 2008 IEEE Conference on Computer Vision and Pattern Recognition.
[35] Kenneth E. Barner,et al. A Computationally Efficient Super-Resolution Algorithm for Video Processing Using Partition Filters , 2007, IEEE Transactions on Circuits and Systems for Video Technology.
[36] M. Schubert,et al. Photoluminescence imaging of silicon wafers , 2006 .
[37] Zhou Wang,et al. Modern Image Quality Assessment , 2006, Modern Image Quality Assessment.
[38] T. Fuyuki,et al. Photographic surveying of minority carrier diffusion length in polycrystalline silicon solar cells by electroluminescence , 2005 .
[39] Moon Gi Kang,et al. Super-resolution image reconstruction: a technical overview , 2003, IEEE Signal Process. Mag..
[40] R. Keys. Cubic convolution interpolation for digital image processing , 1981 .
[41] C. Duchon. Lanczos Filtering in One and Two Dimensions , 1979 .
[42] W. Schottky. Über spontane Stromschwankungen in verschiedenen Elektrizitätsleitern , 1918 .