COVID-MTL: Multitask Learning with Shift3D and Random-weighted Loss for Automated Diagnosis and Severity Assessment of COVID-19

no code implementations • 10 Dec 2020 • Guoqing Bao, Huai Chen, Tongliang Liu, Guanzhong Gong, Yong Yin, Lisheng Wang, Xiuying Wang

In this paper, we present an end-to-end multitask learning (MTL) framework (COVID-MTL) that is capable of automated and simultaneous detection (against both radiology and NAT) and severity assessment of COVID-19.

COVID-19 Diagnosis Transfer Learning

Depthwise Multiception Convolution for Reducing Network Parameters without Sacrificing Accuracy

1 code implementation • 7 Nov 2020 • Guoqing Bao, Manuel B. Graeber, Xiuying Wang

We have carried out the experiment on four benchmark datasets, i. e. Cifar-10, Cifar-100, STL-10 and ImageNet32x32, using five popular CNN models, Multiception achieved accuracy promotion in all models and demonstrated higher accuracy performance compared to related works.