Thông tin tài liệu
Nhan đề : |
A pre-trained convolutional neural network with optimized capsule networks for chest X-rays COVID-19 diagnosis |
Tác giả : |
Lobna M., AbouEl-Magd Ashraf, Darwish Vaclav Snasel, Snasel |
Năm xuất bản : |
2023 |
Nhà xuất bản : |
Springer |
Tóm tắt : |
Coronavirus disease (COVID-19) is rapidly spreading worldwide. Recent studies show that radiological images contain accurate data for detecting the coronavirus. This paper proposes a pre-trained convolutional neural network (VGG16) with Capsule Neural Networks (CapsNet) to detect COVID-19 with unbalanced data sets. The CapsNet is proposed due to its ability to define features such as perspective, orientation, and size. Synthetic Minority Over-sampling Technique (SMOTE) was employed to ensure that new samples were generated close to the sample center, avoiding the production of outliers or changes in data distribution. |
Mô tả: |
CC BY |
URI: |
https://link.springer.com/article/10.1007/s10586-022-03703-2 https://dlib.phenikaa-uni.edu.vn/handle/PNK/7371 |
Bộ sưu tập |
OER - Công nghệ thông tin |
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