Deep Learning Approach for COVID-19 Identification
- Resource Type
- Conference
- Authors
- Ul Haq, Amin; Li, Jian Ping; Khan, Riaz Ullah; Mawuli, Cobbinah Bernard; Agbley, Bless Lord Y.; Raj, Mordecai F.; Zhou, Wang; Khan, Jalaluddin; Haq, Abdul; Saboor, Abdus; Habib, Faiza; Khan, Zafar
- Source
- 2021 18th International Computer Conference on Wavelet Active Media Technology and Information Processing (ICCWAMTIP) Wavelet Active Media Technology and Information Processing (ICCWAMTIP), 2021 18th International Computer Conference on. :154-156 Dec, 2021
- Subject
- Computing and Processing
Robotics and Control Systems
Signal Processing and Analysis
COVID-19
Deep learning
Image recognition
Computational modeling
Medical services
Information processing
Media
Detection
CNN
Chest X-ray image data
Analsis
- Language
- ISSN
- 2576-8964
Accurate diagnostic system is significantly important for timely COVID-19 identification. Diagnosing COVID-19 from chest x-ray images employing the CNN model is recommended for accurate recognition of COVID-19. The existing diagnosis techniques of COVID-19 still lack high accuracy. To handle this problem in this work, we have proposed accurate detection method for COVID-19. In the proposed method, a CNN is incorporated for the diagnosis of COVID-19 using chest x-ray images data. The experimental results illustrate that our technique is good for COVID-19 accurate diagnosis and can be easily implemented in health care systems.