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Covid-19 detection via deep neural network and occlusion sensitivity maps
  • Noor Ahmad ,
  • Muhammad Aminu ,
  • Mohd Halim Mohd Noor
Noor Ahmad
Universiti Sains Malaysia

Corresponding Author:[email protected]

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Muhammad Aminu
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Mohd Halim Mohd Noor
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Deep learning approaches have attracted a lot of attention in the automatic detection of Covid-19 and transfer learning is the most common approach. However, majority of the pre-trained models are trained on color images, which can cause inefficiencies when fine-tuning the models on Covid-19 images which are often grayscale. To address this issue, we propose a deep learning architecture called CovidNet which requires a relatively smaller number of parameters. CovidNet accepts grayscale images as inputs and is suitable for training with limited training dataset. Experimental results show that CovidNet outperforms other state-of-the-art deep learning models for Covid-19 detection.