Convolutional neural network with median layers for denoising salt-and-pepper contaminations

Author:

Liang Luming,Deng Seng,Gueguen Lionel,Wei Mingqiang,Wu Xinming,Qin Jing

Funder

National Natural Science Foundation of China

Publisher

Elsevier BV

Subject

Artificial Intelligence,Cognitive Neuroscience,Computer Science Applications

Reference19 articles.

1. Beyond a Gaussian denoiser: Residual learning of deep CNN for image denoising;Zhang;IEEE Trans. Image Process.,2017

2. K. Zhang, W. Zuo, L. Zhang, Ffdnet: Toward a fast and flexible solution for CNN based image denoising, IEEE Transactions on Image Processing.

3. D. Liu, B. Wen, X. Liu, Z. Wang, T. Huang, When image denoising meets high-level vision tasks: A deep learning approach, in: Proceedings of the Twenty-Seventh International Joint Conference on Artificial Intelligence, IJCAI-18, International Joint Conferences on Artificial Intelligence Organization, 2018, pp. 842–848. doi:10.24963/ijcai.2018/117. https://doi.org/10.24963/ijcai.2018/117.

4. A convolutional neural networks denoising approach for salt and pepper noise;Fu;Multimedia Tools Appl.,2018

5. J. Lehtinen, J. Munkberg, J. Hasselgren, S. Laine, T. Karras, M. Aittala, T. Aila, Noise2noise: Learning image restoration without clean data, in: International Conference on Machine Learning (ICML) 2018, 2018, pp. 2971–2980.

Cited by 25 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. Generalized multilevel B-spline approximation for scattered data interpolation in image processing;Applied Mathematical Modelling;2024-10

2. Context Aware CNN approach to denoise Salt and Pepper Images;2024 IEEE International Conference on Interdisciplinary Approaches in Technology and Management for Social Innovation (IATMSI);2024-03-14

3. Monochrome Image Impulse Noise Removal Considering Line Structure;Lecture Notes in Computer Science;2024

4. A comprehensive review of image denoising in deep learning;Multimedia Tools and Applications;2023-12-20

5. Study on salt-and-pepper denoising based on dual convolutional neural networks;2023 5th International Academic Exchange Conference on Science and Technology Innovation (IAECST);2023-12-08

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3