In this study, the robustness of CNN models was investigated by using the cross-entropy, pseudo-Huber, and correntropy loss functions on noisy data. The ...
Feb 1, 2021 · In this study, the robustness of CNN models was investigated by using the cross-entropy, pseudo-Huber, and cor- rentropy loss functions on noisy ...
Robustness of convolutional neural network models in hyperspectral noisy datasets with loss functions ... functions under label noise for deep neural networks ...
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This study proposes a novel CNN architecture for baby cry recognition under varying noise conditions, featuring three convolutional layers, a max pooling layer, ...
A fast hyperspectral image classification algorithm with strong noise robustness is proposed in this paper, aiming at the hyperspectral image classification ...
Image noise can decrease classification performance and increase network training time. This research was tested the robustness of two CNN methods, namely VGG16 ...
Aug 4, 2020 · This study aimed to investigate the robustness of deep convolutional neural networks (CNNs) for binary classification of posteroanterior chest x ...
Missing: hyperspectral | Show results with:hyperspectral
6 days ago · Robustness of convolutional neural network models in hyperspectral noisy datasets with loss functions. Computers and Electrical Engineering ...
It enhances its model robustness to noisy labels to a great extent by employing a novel dual-channel structure and a noise-robust loss function. In this way, ...
For example, Ghafari et al. [12] investigated the robustness of convolutional neural networks by evaluating the performance of different loss functions, ...