Abstract
This chapter concludes the present work by collectively comparing the performance of the different computer-aided classification (CAC) systems designed. It also discusses the future work that involves other convolution neural network (CNN) models, such as VGGNet and ResNet-50, and other variants, such as DarkNet and NasNet. These CNN models can be used to design similar CAC systems for the binary classification of chest radiographs as designed in the present work. These CAC systems could be designed for multiclass classification such as the three-class classification of chest radiographs into Normal, Pneumonia, and COVID-19 classes.
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
