计算机科学与技术的教育经历,计算机科学与技术学院

计算机科学与技术的教育经历,计算机科学与技术学院"/>

计算机科学与技术的教育经历,计算机科学与技术学院

L. Chen, J. Zhang, S. Lin,F. Fang, J. Ren, “Blind Deblurring for Saturated Images”,IEEE Conference on Computer Vision and PatternRecognition (CVPR), 2021. (CCF A)

L. Chen, J. Zhang, J. Pan, S. Lin,F. Fang, J. Ren, “Learning a Non-blind Deblurring Network for Night Blurry Images”, IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2021. (CCF A)

Y. Yuan,F. Fang, and G. Zhang, “Superpixelbased Seamless Image Stitching for UAV Images,” IEEE Transactions on Geoscience and Remote Sensing (TGRS)，59(2):1565-1576, 2021.(SCI一区)

F. Fang, J. Li, Y. Yuan, T. Zeng and G. Zhang, “Multilevel Edge Features Guided Network for Image Denoising,” IEEE Transactions on Neural Networks and Learning Systems (TNNLS), 2020. (SCI一区)

J. Li, J. Li, F. Fang, F. Li and G. Zhang, “Luminance-aware Pyramid Network for Low-light Image Enhancement,” IEEE Transactions on Multimedia (TMM), 2020. (SCI一区)

J. Li, F. Fang, J. Li, K. Mei and G. Zhang, “MDCN: Multi-scale Dense Cross Network for Image Super-Resolution,” IEEE Transactions on Circuits and Systems for Video Technology (TCSVT), 2020. (SCI二区)

F. Fang, J. Li, T. Zeng, “Soft-Edge Assisted Network for Single Image Super-Resolution”, IEEE Transactions on Image Processing (TIP), vol. 29, pp. 4656-4668, 2020. (CCF A)

F. Fang,T. Wang, T. Zeng and G. Zhang, “A Superpixel-Based Variational Model for Image Colorization,” IEEE Transactions on Visualization and Computer Graphics (TVCG), vol. 26, no. 10, pp. 2931-2943, 2020. (CCF A)

Z. Xu, T. Wang, F. Fang, Y. Shen, G. Zhang. “Stylization-Based Architecture for Fast Deep Exemplar Colorization”, IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2020, pp. 9363-9372. (CCFA)

F. Fang, T. Wang, S. Wu, and G. Zhang, “Removing Moire Patterns from Single Images”, Information Sciences, vol. 514, pp. 56–70, 2020. (SCI一区)

F. Fang, T. Wang, Y. Wang, T. Zeng, and G. Zhang, Variational Single Image Dehazing for Enhanced Visualization, IEEE Transactions on Multimedia (TMM)，vol. 22, no. 10, pp. 2537-2550, 2020. (SCI一区)

Z. Gu, F. Li, F. Fang, and G. Zhang, “A Novel Retinex-based Fractional-order Variational Model for Images with Severely Low Light”, IEEE Transactions on Image Processing (TIP), vol. 29, pp. 3239-3253, 2020. (CCF A)

L. Chen, F. Fang, J. Liu, G. Zhang, “OID: Outlier Identifying and Discarding in Blind Image Deblurring”, The European Conference on Computer Vision (ECCV), 598-613, 2020. (CCF B)

L. Chen, F. Fang, S. Lei, F. Li, and G. Zhang, “Enhanced Sparse Model for Blind Deblurring,” The European Conference on Computer Vision (ECCV), 631–646, 2020. (CCF B)

H. Zhen, F. Fang, and G. Zhang, “Cascaded Dilated Dense Network with Two-step Data Consistency for MRI Reconstruction”, 33rd Conference on Neural Information Processing Systems (NeurIPS2019), 2019. (CCF A)

L. Chen, F. Fang, T. Wang, and G. Zhang, “Blind Image Deblurring with Local Maximum Gradient Prior,” IEEE Conference on Computer Vision and Pattern Recognition 2019 (CVPR 2019), pp. 1742-1750, 2019. (CCF A)

T. Wang, F. Fang, F. Li, and G. Zhang, “High Quality Bayesian Pansharpening,” IEEE Transactions on Image Processing (TIP), vol. 28, no. 1, pp. 227-239, 2019. (CCF A)

J. Li, F. Fang, K. Mei, and G. Zhang, “Multi-scale Residual Network for Image Super-Resolution,” The European Conference on Computer Vision (ECCV), pp. 517-532, 2018. (CCF B)

Faming Fang, Fang Li, and Tieyong Zeng,Reducing spatially varying out-of-focus blur from natural image, Inverse Problems and Imaging,11(1),65-85,2017.

Dehao Shang, Tingting Wang, and Faming Fang,Single image dehazing using holder coefficient, in 2016 International Conference on Knowledge Science, Engineering and Management. Passau, Germany: Springer, 314-324, 2016.

Guixu Zhang, Yingying Xu, and Faming Fang, Framelet based sparse unmixing of hyperspectral images, IEEE Transaction on Image Processing, 25(4), 1516-1529,2016.

Fang Li, Faming Fang, and Guixu Zhang,Unsupervised change detection in SAR images using curvelet and L1-norm based soft segmentation, International Journal of Remote Sensing, 37, 3232-3254, 2016.

Yingying Xu, Faming Fang, and Guixu Zhang,Similarity-guided and Lp-regularized sparse unmixing of hyperspectral data, IEEE Geoscience and Remote Sensing Letters, 12, 2311-2315,2015.

Yang Xiao, Faming Fang, Qian Zhang, Aimin Zhou,and Guixu Zhang, Parameter selection for variational pan-sharpening by using evolutionary algorithm, Remote Sensing Letters, 6, 458-467,2015.

Guixu Zhang, Faming Fang, Fang Li, and Chaomin Shen,Pan-sharpening of multi-spectral images using a new variational model, International Journal of Remote Sensing, 36(5), 1484-1508,2015.

Chunzhi Li, Aimin Zhou, Guixu Zhang, and Faming Fang, An antinoise method for hyper-spectral unmixing, IEEE Geoscience and Remote Sensing Letters, 12(3), 1484-1508,2015.

Shizhang Tang, Faming Fang,and Guixu Zhang, Variational approach for multi-source image fusion, IET Image Processing, 9, 134-141,2015.

Faming Fang, Fang Li and Tieyong Zeng*. Single image dehazing and denoising: A fast variational approach,SIAM Journal on Imaging Sciences, 7(2), 969–964, 2014.

Faming Fang, Guixu Zhang, Fang Li and Chaomin Shen. Framelet based pan-sharpening via a variational method. Neurocomputing, 129, 362–377, 2014.

Chunzhi Li, Faming Fang, Aimin Zhou, and Guixu Zhang, A novel blind spectral unmixing method based on error analysis of linear mixture model, IEEE Geoscience and Remote Sensing Letters, 11(7), 1180-1184,2014.

Faming Fang, Fang Li, Chaomin Shen and Guixu Zhang. A variational approach for pan-sharpening, IEEE Transactions on Image Processing, 22(7), 2822-2834, 2013.

Faming Fang, Fang Li, Guixu Zhang and Chaomin Shen. A variational method for multisource remote-sensing image fusion. International Journal of Remote Sensing, 34, 2470–2486, 2013.

Huiyan Liu,Fengxia Yan,Jubo Zhu,and Faming Fang, Adaptive vectorial total variation models for multi-channel SAR images despeckling with fast algorithms, IET Image Processing,7(9), 795–804,2013.

Huiyan Liu, Jiying Liu, Fengxia Yan, Jobo Zhu, and Faming Fang,Spatially adapted total variational model for synthetic aperture radar image despeckling, Journal of Electronic Imaging,22(3), 033019, 2013.