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Detecting COVID-19 in Chest X-Ray Images Using Apache Spark and CNN
2022 12th International Workshop on Computer Science and Engineering, WCSE 2022 ; : 207-211, 2022.
Article in English | Scopus | ID: covidwho-2025939
ABSTRACT
COVID-19 is highly contagious and highly pathogenic, It seriously threatens human life and health. Rapid detection of positive COVID-19 cases is very important in stopping the spread of the virus. At early diagnosis, It is the most simple and rapid indicator for judging changes in the illness. As the COVID-19 chest X-ray image dataset continues to expand, Researchers build a CNN-based COVID-19 detection model on Apache Spark. The model can effectively detect positive cases of COVID-19. This article first introduces the big data platform Apache Spark, Deep Learning Technology CNN, transfer learning techniques, etc. Then, it summarizes the characteristics and deficiencies of the research on chest X-ray image recognition of COVID-19 in recent years. Finally, Under the big data thinking, This paper proposes a technical direction for rapid detection of COVID-19 based on the big data analysis platform Apache Spark and the deep learning algorithm CNN for large-scale COVID-19 chest X-ray image datasets. © 2022 WCSE. All Rights Reserved.
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Full text: Available Collection: Databases of international organizations Database: Scopus Language: English Journal: 2022 12th International Workshop on Computer Science and Engineering, WCSE 2022 Year: 2022 Document Type: Article

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Full text: Available Collection: Databases of international organizations Database: Scopus Language: English Journal: 2022 12th International Workshop on Computer Science and Engineering, WCSE 2022 Year: 2022 Document Type: Article