Journal of Textile Research ›› 2020, Vol. 41 ›› Issue (07): 40-46.doi: 10.13475/j.fzxb.20191102407
• Textile Engineering • Previous Articles Next Articles
SHAO Jinxin1, ZHANG Baochang1,2(), CAO Jipeng3
CLC Number:
[1] | 于学智, 邵英海, 曹继鹏. 刺辊速度对梳理后纤维长度指标的影响[J]. 棉纺织技术, 2016,44(3):26-29. |
YU Xuezhi, SHAO Yinghai, CAO Jipeng. Influence of licker-in speed on fiber length index after carding[J]. Cotton Textile Technology, 2016,44(3):26-29. | |
[2] | 何晓峰, 徐守东, 刘从九. 棉纤维细度检测技术综述[J]. 中国纤检, 2018(10):88-93. |
HE Xiaofeng, XU Shoudong, LIU Congjiu. Summary of cotton fiber fineness detection technology[J]. China Fiber Inspection, 2018 (10):88-93. | |
[3] | 刘天骄, 孙润军, 王红红. 利用激光细度仪快速检测棉纤维细度的探究[J]. 棉纺织技术, 2018,46(3):77-80. |
LIU Tianjiao, SUN Runjun, WANG Honghong. Study on rapid detection of cotton fiber linear density with the laserscan[J]. Cotton Textile Technology, 2018,46(3):77-80. | |
[4] | LIU K, TAN J, SU B. An adaptive image denoising model based on Tikhonov and TV regularizations[J]. Advances in Multimedia, 2014,2014:1-10. |
[5] | LIU P, ZHANG H, ZHANG K, et al. Multi-level wavelet-CNN for image restoration[C] //Proceedings of the IEEE conference on computer vision and pattern recognition workshops. Salt Lake: Computer Vision Foundation, 2018: 773-782. |
[6] | 刘亚梅. 基于梯度边缘最大值的图像清晰度评价[J]. 图学学报, 2016,37(2):97-102. |
LIU Yamei. Sharpness assessment for remote sensing image based on maximum gradient[J]. Journal of Graphics, 2016,37(2):97-102. | |
[7] | 孙旭, 李晓光, 李嘉锋, 等. 基于深度学习的图像超分辨率复原研究进展[J]. 自动化学报, 2017,43(5):697-709. |
SUN Xu, LI Xiaoguang, LI Jiafeng, et al. Review on deep learning based image super-resolution restoration algorithms[J]. Acta Automatica Sinica, 2017,43(5):697-709. | |
[8] |
DONG C, LOY C C, HE K, et al. Image super-resolution using deep convolutional networks[J]. IEEE Transactions on Pattern Analysis and Machine Intelligence, 2015,38(2):295-307.
doi: 10.1109/TPAMI.2015.2439281 pmid: 26761735 |
[9] |
YANG J, WRIGHT J, HUANG T S, et al. Image super-resolution via sparse representation[J]. IEEE Transactions on Image Processing, 2010,19(11):2861-2873.
pmid: 20483687 |
[10] | VIJAYARANI S, VINUPRIYA M. Performance analysis of canny and sobel edge detection algorithms in image mining[J]. International Journal of Innovative Research in Computer and Communication Engineering, 2013,1(8):1760-1767. |
[11] | GALUN M, BASRI R, BRANDT A. Multiscale edge detection and fiber enhancement using differences of oriented means[C] //2007 IEEE 11th International Conference on Computer Vision. Rio de Janeiro:IEEE, 2007: 1-8. |
[12] | 颜贝, 张建林. 基于生成对抗网络的图像翻译现状研究[J]. 国外电子测量技术, 2019,38(6):130-134. |
YAN Bei, ZHANG Jianlin. Research the status of image translation based on generative adversarial networks[J]. Foreign Electronic Measurement Technology, 2019,38(6):130-134. | |
[13] | CRESWELL A, WHITE T, DUMOULLIN V, et al. Generative adversarial networks: an overview[J]. IEEE Signal Processing Magazine, 2018,35(1):53-65. |
[14] | SALIMANS T, GOODFELLOW I, ZAREMBA W, et al. Improved techniques for training GANs[C] //Advances in Neural Information Processing Systems. Barcelona: Curran Associates, 2016: 2234-2242. |
[15] | ZHU J Y, PARK T, ISOLA P, et al. Unpaired image-to-image translation using cycle-consistent adversarial networks[C] //Proceedings of the IEEE International Conference on Computer Vision. Venice: Computer Vision Foundation, 2017: 2223-2232. |
[1] | . Concave points matching and segmentation algorithm for overlapped fiber image [J]. JOURNAL OF TEXTILE RESEARCH, 2017, 38(11): 143-149. |
[2] | . Level set of central axis method of cashmere and wool diameter [J]. JOURNAL OF TEXTILE RESEARCH, 2017, 38(09): 14-18. |
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