Zobrazeno 1 - 10
of 33
pro vyhledávání: '"Chunjiang Duanmu"'
Autor:
Chunjiang Duanmu, Junjie Zhu
Publikováno v:
IEEE Access, Vol 8, Pp 140599-140606 (2020)
The deep learning technique has been recently used in the image super-resolution. When the deep learning network is too deep, it is difficult to train this network to make it converge. Furthermore, the problem of gradient loss occurs for a very deep
Externí odkaz:
https://doaj.org/article/25f11e3507a346d29a360668dadf671c
Publikováno v:
IEEE Access, Vol 6, Pp 26707-26717 (2018)
A method is proposed, called l-formula, to design efficient successive cancellation (SC) decoding of polar codes with medium-dimensional binary kernels (dimensions up to 16). Our l-formula method obtains the simplified recursive formulas of the SC de
Externí odkaz:
https://doaj.org/article/abbc938f5ddb4243853cacaeabf246ca
Autor:
Junjie Zhu, Chunjiang Duanmu
Publikováno v:
IEEE Access, Vol 8, Pp 140599-140606 (2020)
The deep learning technique has been recently used in the image super-resolution. When the deep learning network is too deep, it is difficult to train this network to make it converge. Furthermore, the problem of gradient loss occurs for a very deep
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::a2eae4354218ba5321cb1d3af50ff6f2
https://ieeexplore.ieee.org/document/9153565/
https://ieeexplore.ieee.org/document/9153565/
Publikováno v:
In Information Sciences 2008 178(9):2215-2223
Publikováno v:
IEEE Access, Vol 6, Pp 26707-26717 (2018)
A method is proposed, called $l$ -formula, to design efficient successive cancellation (SC) decoding of polar codes with medium-dimensional binary kernels (dimensions up to 16). Our $l$ -formula method obtains the simplified recursive formulas of the
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::c15f1715d83e6c76be8d9bc720a6294f
https://ieeexplore.ieee.org/document/8355997/
https://ieeexplore.ieee.org/document/8355997/
Autor:
Yi Lei, ChunJiang DuanMu
Publikováno v:
Second Target Recognition and Artificial Intelligence Summit Forum.
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::9cbd964e79ffd32a366b8720a21ae385
https://doi.org/10.1117/12.2550456
https://doi.org/10.1117/12.2550456
Publikováno v:
Engineering Applications of Artificial Intelligence. 48:204-229
The proposed algorithm, which uses partial differential equations (PDE) and generalized cross validation (GCV) theory in the tetrolet transform domain, is used to reduce the noise in an image. Tetrolet transform is applied to decompose the noisy imag
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::0e1bc6ce63f4203d1a0cabd3f1fdf00d
https://doi.org/10.1016/j.engappai.2015.10.008
https://doi.org/10.1016/j.engappai.2015.10.008
Autor:
Chunjiang Duanmu, Zhe Zheng
Publikováno v:
Journal of Physics: Conference Series. 1693:012170
In order to enhance the visual effects of the reconstructed images in the single image super-resolution, and solve the problem of instability of the training phase of super-resolution with generative adversary network (SRGAN), a new super-resolution
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::64c1093bc1dcd6605f28e20cdc254d01
https://doi.org/10.1088/1742-6596/1693/1/012170
https://doi.org/10.1088/1742-6596/1693/1/012170
Autor:
Kai Wang, Chunjiang Duanmu
Publikováno v:
Journal of Physics: Conference Series. 1651:012167
Rcently, the research of single image super-resolution (SISR) based on deep learning has made great progress. However, most of the methods of super-resolution (SR) study use a simple chain structure to obtain higher super-resolution performance. Addi
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::7cd6e4bd7a47faf97479a1668677946d
https://doi.org/10.1088/1742-6596/1651/1/012167
https://doi.org/10.1088/1742-6596/1651/1/012167
Autor:
Feiyan Zhang, Chunjiang DuanMu
Publikováno v:
Journal of Applied Remote Sensing. 14:1
Fusion results of low-resolution multispectral (LRMS) images and high-resolution panchromatic (Pan) images, also called pan-sharpened images, are always difficult to evaluate due to the lack of high-resolution multispectral (HRMS) images and the comp
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::fe30b22a2e8078d1de8cf174d8b41db3
https://doi.org/10.1117/1.jrs.14.026513
https://doi.org/10.1117/1.jrs.14.026513