Therefore, to prevent the spread and reduce the negative impact of COVID-19, an accurate and fast test is needed. Until now, there has been no medicine that can completely cure COVID-19. ![]() This disease has a negative impact on individuals, governments, and even the global economy, which has caused the WHO to declare COVID-19 as a PHEIC (Public Health Emergency of International Concern). The n-sigmoid SE block not only reduces the vanishing gradient problem but also develops valuable features by combining channel-wise and spatial information.ĬOVID-19 is the disease that has spread over the world since December 2019. Experiments conducted using SE showed that the new n-sigmoid function results in performance improvements in the training accuracy score for UNet (up 0.25% to 99.67%), ResNet (up 0.9% to 95.1%), and DenseNet (up 1.1% to 98.87%) for the 2D cases, and the 3D UNet (up 0.2% to 99.67%) for the 3D cases. To evaluate the performance of this new method, commonly used datasets, CIFAR-10 and Carvana for 2D data and Sandstone Dataset for 3D data, were considered. Comparisons were made between the networks with the original design, the addition of the SE block, and the proposed n-sigmoid SE block. The proposed activation function aims to improve the learning and generalization capacity of 2D and 3D neural networks for classification and segmentation, by reducing the vanishing gradient problem. ![]() The purpose of this paper is to further improve the network by introducing a new SE block with a custom activation function resulting from the integration of a piecewise shifted sigmoid function. However, the various sigmoid functions used in artificial neural networks are intrinsically restricted by vanishing gradients. ![]() SE structures are generally adopted in a plethora of tasks directly in existing models and have shown actual performance enhancements. The Squeeze-and-Excitation (SE) structure has been designed to enhance the neural network performance by allowing it to execute positive channel-wise feature recalibration and suppress less useful features.
0 Comments
Leave a Reply. |
AuthorWrite something about yourself. No need to be fancy, just an overview. ArchivesCategories |