ArticleIEEE sensors journal2022
AVNC: Attention-Based VGG-Style Network for COVID-19 Diagnosis by CBAM.
Article in IEEE sensors journal, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 21 papers.
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Who cites it
21 citing papers in PubMed.
- Character generation and visual quality enhancement in animated films using deep learning.Scientific reports · 2025Article
- Transfer Learning-Based Classifier to Automate the Extraction of False X-Ray Images From Hospital's Database.International dental journal · 2024Article
- SSG-Net: A Multi-Branch Fault Diagnosis Method for Scroll Compressors Using Swin Transformer Sliding Window, Shallow ResNet, and Global Attention Mechanism (GAM).Sensors (Basel, Switzerland) · 2024Article
- PS5-Net: a medical image segmentation network with multiscale resolution.Journal of medical imaging (Bellingham, Wash.) · 2024Article
- Electrophysiological analysis of ENG signals in patients with Covid-19.IBRO neuroscience reports · 2023Article
- IRCM-Caps: An X-ray image detection method for COVID-19.The clinical respiratory journal · 2023Article
- Deep-Learning-Based COVID-19 Diagnosis and Implementation in Embedded Edge-Computing Device.Diagnostics (Basel, Switzerland) · 2023Article
- YOLOv7-RAR for Urban Vehicle Detection.Sensors (Basel, Switzerland) · 2023Article
- A framework to distinguish healthy/cancer renal CT images using the fused deep features.Frontiers in public health · 2023Article
- Interactive method research of dual mode information coordination integration for astronaut gesture and eye movement signals based on hybrid model.Science China. Technological sciences · 2023Article
- A Survey on Deep Learning in COVID-19 Diagnosis.Journal of imaging · 2022Review
- McS-Net: Multi-class Siamese network for severity of COVID-19 infection classification from lung CT scan slices.Applied soft computing · 2022Article
- COVID-19 detection based on pre-trained deep networks and LSTM model using X-ray images enhanced contrast with artificial bee colony algorithm.Expert systems · 2022Article
- Intelligent Identification of Jute Pests Based on Transfer Learning and Deep Convolutional Neural Networks.Neural processing letters · 2022Article
- On the performance evaluation of object classification models in low altitude aerial data.The Journal of supercomputing · 2022Article
- CNN-based bi-directional and directional long-short term memory network for determination of face mask.Biomedical signal processing and control · 2022Article
- A Novel Weighted Consensus Machine Learning Model for COVID-19 Infection Classification Using CT Scan Images.Arabian journal for science and engineering · 2021Article
- Integration and Segregation of Dynamic Functional Connectivity States for Mild Cognitive Impairment Revealed by Graph Theory Indicators.Contrast media & molecular imaging · 2021Article
- Automatic Segmentation of Novel Coronavirus Pneumonia Lesions in CT Images Utilizing Deep-Supervised Ensemble Learning Network.Frontiers in medicine · 2021Article
- AIoT Used for COVID-19 Pandemic Prevention and Control.Contrast media & molecular imaging · 2021Review
Corrections and comments
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Authors and funding
4 authors.
Funding
Abstract
(Aim) To detect COVID-19 patients more accurately and more precisely, we proposed a novel artificial intelligence model. (Methods) We used previously proposed chest CT dataset containing four categories: COVID-19, community-acquired pneumonia, secondary pulmonary tuberculosis, and healthy subjects. First, we proposed a novel VGG-style base network (VSBN) as backbone network. Second, convolutional block attention module (CBAM) was introduced as attention module into our VSBN. Third, an improved multiple-way data augmentation method was used to resist overfitting of our AI model. In all, our model was dubbed as a 12-layer attention-based VGG-style network for COVID-19 (AVNC) (Results) This proposed AVNC achieved the sensitivity/precision/F1 per class all above 95%. Particularly, AVNC yielded a micro-averaged F1 score of 96.87%, which is higher than 11 state-of-the-art approaches. (Conclusion) This proposed AVNC is effective in recognizing COVID-19 diseases.
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