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Poisson noise and Gaussian noise separation through copula theory
This study explores an innovative optimization problem in copula denoising, aiming to distinguish and eliminate both Poisson noise and Gaussian...
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Structural similarity-based Bi-representation through true noise level for noise-robust face super-resolution
In today’s real-world scenarios’ of computer vision applications, enhancing low-resolution (LR) facial images corrupted with unwanted noise effects...
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The Need for Noise
In this chapter, we'll be covering the limitations of the random functions we've utilized thus far and how these limitations can be addressed by...
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Noise4Denoise: Leveraging noise for unsupervised point cloud denoising
Existing deep learning-based point cloud denoising methods are generally trained in a supervised manner that requires clean data as ground-truth...
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Label distribution similarity-based noise correction for crowdsourcing
In crowdsourcing scenarios, we can obtain each instance’s multiple noisy labels from different crowd workers and then infer its integrated label via...
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Noise level estimation based on eigenvalue learning
At present, many algorithms use a single minimum eigenvalue to estimate the real noise level, and the levels estimated by these algorithms have been...
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Robust enhanced collaborative filtering without explicit noise filtering
Graph convolutional neural networks have been successfully applied to collaborative filtering to capture high-quality user-item representations....
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Learning image blind denoisers without explicit noise modeling
Image blind denoising aims at removing the unknown noise from given images to improve the image’s visual quality. Current blind denoisers can be...
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Noise-aware progressive multi-scale deepfake detection
The proliferation of fake images generated by deepfake techniques has significantly threatened the trustworthiness of digital information, leading to...
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An effective adaptive fuzzy filter for speckle noise reduction
SAR is a self-illuminating imaging method that produces high-resolution images in all weather conditions, day and night. Many application scientists...
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Integer syndrome decoding in the presence of noise
Code-based cryptography received attention after the NIST started the post-quantum cryptography standardization process in 2016. A central NP-hard...
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Noise cleaning for nonuniform ordinal labels based on inter-class distance
Label noise poses a significant challenge to supervised learning algorithms. Extensive research has been conducted on classification and regression...
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Speckle Noise Removal: A Local Structure Preserving Approach
This paper proposes a speckle noise removal approach for clinical ultrasound images by doing outlier removal and smoothening operations alternately....
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Overhead-free Noise-tolerant Federated Learning: A New Baseline
Federated learning (FL) is a promising decentralized machine learning approach that enables multiple distributed clients to train a model jointly...
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Nrat: towards adversarial training with inherent label noise
Adversarial training (AT) has been widely recognized as the most effective defense approach against adversarial attacks on deep neural networks and...
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Iterative shrinkage thresholding-based anti-multi-noise compression perceptual image reconstruction network
Telemedicine imaging services usually require wireless transmission of a large number of medical images MRI/CT, etc., in the network, which are...
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Exploring the potential of parallel adaptive filters for audio noise removal
This paper presents a novel adaptive structure for audio noise removal, aiming to enhance the performance of noise reduction. The proposed structure...
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Low-resolution Kramers-Kronig detection system with error-feedback noise sha**
In this paper, we investigated the effects of error-feedback noise sha** (EFNS) on a low-resolution Kramers-Kronig (KK) detection system for the...
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A nonlocal model for image restoration corrupted by multiplicative noise
In the field of image processing, addressing multiplicative noise, particularly when it follows the Gamma distribution, has been the subject of...
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A noise level estimation method of impulse noise image based on local similarity
The detection and removal methods of impulse noise often need to estimate the noise level of the damaged image in advance to obtain a better...
