References

[1] Rishit Dagli and Ali Mustufa Shaikh. Cppe-5: Medical personal protective equipment dataset. arXiv preprint arXiv:2112.09569, 2021.


[2] Tsung-Yi Lin,Michael Maire,Serge Belongie,Lubomir Bourdev,Ross Girshick,James Hays,Pietro Perona, Deva Ramanan, C. Lawrence Zitnick, and Piotr Doll ́ar. Microsoft coco: Common objects in context, 2015.


[3] Ghorbani a, ouyang d, abid a, he b, chen jh, harrington ra, liang dh, ashley ea, zou jy. deep learning interpretation of echocardiograms. npj digit med.2020 jan 24;3:10. doi: 10.1038/s41746-019-0216-8. pmid: 31993508; pmcid: Pmc6981156.


[4] Haibo Wang, Angel Cruz-Roa, Ajay Basavanhally,Hannah Gilmore, Natalie Shih, Michael Feldman,John E. Tomaszewski, Fabio A. Gonz ́alez,andAnant Madabhushi.Mitosis detection in breast cancer pathology images by combining handcrafted and convolutional neural network features. Journal of medical imaging (Bellingham, Wash.), 1(3):034003–034003, October 2014.


[5] Dan C. Cireşan, Alessandro Giusti, Luca M. Gambardella, and J ̈urgen Schmidhuber.Mitosis de-tection in breast cancer histology images with deep neural networks. In Kensaku Mori, Ichiro Sakuma, Yoshinobu Sato, Christian Barillot, and Nassir Navab,editors,Medical Image Computing and Computer-Assisted Intervention – MICCAI 2013

, pages 411–418, Berlin, Heidelberg, 2013. Springer Berlin Heidelberg.


[6] MN Kashif, SEA Raza,K SIRINUKUNWATTANA, M Arif, and N Rajpoot. Handcrafted features with convolutional neural networks for detection of tumor cells in histology images. In 2016 IEEE 13th International Symposium on Biomedical Imaging (ISBI), pages 1029–1032, April 2016.


[7] Loey m,manogaran g, taha mhn, khalifa nem. a hybrid deep transfer learning model with machine learning methods for

face mask detection in the era of the covid-19 pandemic. measurement (lond). 2021;167:108288. doi:10.1016/j.measurement.2020.108288.


[8] Haibo He and Edwardo A. Garcia. Learning from imbalanced data. IEEE Transactions on Knowledge and Data Engineering, 21(9):1263–1284, 2009.