We devote our efforts to investigate the effects of noisy images when using deep convolutional neural networks in classification tasks. There are papers inves-.
Feb 4, 2018 · In this paper, we evaluate the generalization of models learned by different networks using noisy images. Our results show that noise cause the ...
Nov 21, 2024 · The results of this report concluded that training networks with faulty/noisy images is vital to improving the resilience of that network, which ...
An empirical study on the effects of different types of noise in image classification tasks · Computer Science. ArXiv · 2016.
Oct 24, 2018 · We devote our efforts to investigate the effects of noisy images when using deep convolutional neural networks in classification tasks. There ...
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What are the disadvantages of deep convolutional neural network?
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In this paper, a Noise-Robust Convolutional Neural Network (NR-CNN) is proposed to classify the noisy images without any preprocessing for noise removal.
Feb 10, 2023 · In this paper, we proposed a deep CNN model, namely SeConvNet, to suppress SAP noise in gray-scale and color images.
Sep 21, 2020 · This study investigates a deep learning approach to improve the quality of reconstructed image volumes through denoising by a 3D convolution neural network.
In this paper, we analyze some of the common CNNs for degradations in images caused by Gaussian noise, blur as well as compression using JPEG and JPEG 2000.