Scholarlink

COVID-19 is causing a significant increase in deaths worldwide, with a maximum casualty rate of 244,000. The virus affects the pulmonary system severely, leading to critical stages compared to known pneumonia. Identifying COVID-19 symptoms is difficult, and limited testing tools are needed. Preventing the pandemic is crucial, but social gaps and city closures are not effective. COVID-19 affects GDP and health, with the number of affected countries increasing exponentially. Countries like the US, Italy, and France have been beaten by China, causing a negative impact on global revenue. To address this issue, AI-based medical techniques are essential for identifying and treating COVID-19 cases quickly and accurately. Deep learning frameworks, developed over centuries, have shown promising results in healthcare systems, particularly in image datasets like eye images and lung X-rays. This can encourage the development of advanced deep learner frameworks to recognize and diagnose COVID-19 and pneumonia cases globally.

错误：搜索内容不能为空，请输入英文关键词
错误：关键词超出字数限制，请精简
高级检索

COVID Chest Images Detection by Deep Learning and Ensemble Learning

  • 会议论文

  • 发表日期：

    2026年

查看全文
  • Md. Sadab,
  • Deepak Kumar,
  • Aditya,
  • Nikhil

摘要

COVID-19 is causing a significant increase in deaths worldwide, with a maximum casualty rate of 244,000. The virus affects the pulmonary system severely, leading to critical stages compared to known pneumonia. Identifying COVID-19 symptoms is difficult, and limited testing tools are needed. Preventing the pandemic is crucial, but social gaps and city closures are not effective. COVID-19 affects GDP and health, with the number of affected countries increasing exponentially. Countries like the US, Italy, and France have been beaten by China, causing a negative impact on global revenue. To address this issue, AI-based medical techniques are essential for identifying and treating COVID-19 cases quickly and accurately. Deep learning frameworks, developed over centuries, have shown promising results in healthcare systems, particularly in image datasets like eye images and lung X-rays. This can encourage the development of advanced deep learner frameworks to recognize and diagnose COVID-19 and pneumonia cases globally.