A self-validation Noise2Noise training framework for image denoising
Author:
Affiliation:
1. Department of Electrical Engineering, Faculty of Engineering, Prince of Songkla University, Songkhla, Thailand
2. Department of Biomedical Sciences and Biomedical Engineering, Faculty of Medicine, Prince of Songkla University, Songkhla, Thailand
Funder
scholarship awards for master and Ph.D. studies Thailand's education hub for ASEAN countries
Prince of Songkla University
Publisher
Informa UK Limited
Subject
Computer Vision and Pattern Recognition,Media Technology
Link
https://www.tandfonline.com/doi/pdf/10.1080/13682199.2023.2229040
Reference75 articles.
1. Deep learning on image denoising: An overview
2. Ghose S, Singh N, Singh P. Image denoising using deep learning: Convolutional neural network. In 2020 10th International Conference on Cloud Computing, Data Science Engineering (Confluence), pages 511–517, 2020.
3. Rai S, Bhatt JS, Patra SK. An unsupervised deep learning framework for medical image denoising, 2021.
4. Methods for image denoising using convolutional neural network: a review
5. Application of Deep Learning Architectures for Satellite Image Time Series Prediction: A Review
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1. Self-Augmented Noisy Image for Noise2Noise Image Denoising;IEEE Access;2024
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