COVID-19 detection based on Computer Vision and Big Data

Author:

Wu Mark1,Heng Chen2,Zhu Haibin3,Cai Haoyang4

Affiliation:

1. University of Wisconsin - Madison,Madison,United States

2. Northern Arizona University,Arizona,United States

3. Hangzhou Dianzi University,Hangzhou,China

4. The University of Berkeley,Berkeley,United States

Publisher

IEEE

Cited by 5 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. New Artificial Intelligence-based Methods for COVID-19 Diagnosis using Medical Devices;2023 Second International Conference on Augmented Intelligence and Sustainable Systems (ICAISS);2023-08-23

2. From Radiography to Diagnosis: Detecting COVID-19 with Cutting-Edge CT Scans and X-ray Imaging;2023 11th International Conference on Emerging Trends in Engineering & Technology - Signal and Information Processing (ICETET - SIP);2023-04-28

3. TFA-CLSTMNN: Novel convolutional network for sound-based diagnosis of COVID-19;International Journal of Wavelets, Multiresolution and Information Processing;2022-12-19

4. A Dense Layer Stacked CMT-DenseNet Fusion Model for COVID Detection;2022 IEEE International Conference on Cloud Computing in Emerging Markets (CCEM);2022-12-12

5. Comparison between Grad-CAM and EigenCAM on YOLOv5 detection model;2022 International Symposium on Electronics and Smart Devices (ISESD);2022-11-08

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