Department of Mathematical Sciences
|DATE:||Thursday, October 7, 2021|
|TIME:||1:15pm – 2:15pm|
|SPEAKER:||Yifei Zeng, Binghamton University|
chest x-ray images |
In this study, they propose CoroNet, a Deep Convolutional Neural Network model to automati- cally detect COVID-19 infection from chest X-ray images. CoroNet achieved promising results on a small prepared dataset which indicates that given more data, the proposed model can achieve better results with minimum pre-processing of data. Overall, the proposed model substantially advances the current radiology based methodology and during COVID- 19 pandemic, it can be a very helpful tool for clinical practitioners and radiologists to aid them in diagnosis, quantification and follow-up of COVID-19 cases.