Skip to header Skip to main navigation Skip to main content Skip to footer
Home
Academic Citations from Palestine
Foregrounding the Research of Academics in Palestine

Main navigation

  • Home
  • Search
  • About

Efficient Respiratory Disease Classification Using Customized CNN on a Large Kaggle Dataset

Blank
Al-Azhar University – Gaza
Zarandah Q.M.M.; Daud S.M.; Abu-Naser S.S.
Zarandah, Qasem M. M. (58186837000); Daud, Salwani Mohd (60098646400); Abu-Naser, Samy S. (26533902900)
58186837000; 60098646400; 26533902900
2025
Lecture Notes in Networks and Systems
Efficient Respiratory Disease Classification Using Customized CNN on a Large Kaggle Dataset
1537 LNNS
105
117
Bhateja V.; Oroumchian F.; Tang J.; Omar Z.
Springer Science and Business Media Deutschland GmbH
University Malaysia of Computer Science & Engineering (UNIMY), Cyberjaya, Malaysia; Faculty of Engineering and Information Technology, Al-Azhar University, Gaza, Palestine
Zarandah Q.M.M., University Malaysia of Computer Science & Engineering (UNIMY), Cyberjaya, Malaysia; Daud S.M., University Malaysia of Computer Science & Engineering (UNIMY), Cyberjaya, Malaysia; Abu-Naser S.S., Faculty of Engineering and Information Technology, Al-Azhar University, Gaza, Palestine
S.S. Abu-Naser; Faculty of Engineering and Information Technology, Al-Azhar University, Gaza, Palestine; email: abunaser@alazhar.edu.ps
0
10.1007/978-981-96-9242-2_8
Classification; CNN; Respiratory disease
Computer aided diagnosis; Convolutional neural networks; Deep learning; Large datasets; Medical imaging; Pulmonary diseases; Chest X-ray image; Convolutional neural network; Diagnostics tools; Disease classification; Fine tuning; Global health; High quality; Research papers; Training process; Virus disease; Classification (of information)