COVID-19 Disease Detection Using Explainable AI
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Publisher
Springer Nature Singapore
Link
https://link.springer.com/content/pdf/10.1007/978-981-99-5974-7_7
Reference13 articles.
1. Došilović FK, Brčić M, Hlupić N (2018) Explainable artificial intelligence: a survey. In: 2018 41st international convention on information and communication technology, electronics and microelectronics (MIPRO), pp 0210–0215. https://doi.org/10.23919/MIPRO.2018.8400040
2. Hanif A, Hanif A, Wood S (2021) A survey on explainable artificial intelligence techniques and challenges. In: 2021 IEEE 25th international enterprise distributed object computing workshop (EDOCW), pp 81–89. https://doi.org/10.1109/EDOCW52865.2021.00036
3. Soares E, Angelov P, Biaso S, Higa Froes M, Kanda Abe D (2020) SARS-CoV-2 CT-scan dataset: a large dataset of real patients CT scans for SARS-CoV-2 identification. medRxiv (2020). https://doi.org/10.1101/2020.04.24.20078584; Angelov P, Soares E (2020) Towards explainable deep neural networks (xDNN). Neural Netw 130:185–194
4. Irmak E (2020) A novel deep convolutional neural network model for COVID-19 disease detection. In: 2020 medical technologies congress (TIPTEKNO) conference, December 2020. https://doi.org/10.1109/TIPTEKNO50054.2020.9299286
5. Munawar MR (2021) Image classification using convolutional neural networks (CNN). https://medium.com/nerd-for-tech/image-classification-using-convolutional-neural-networks-cnn-eef587ed0c1. Accessed 22 May 2021
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