Comparison of regularization and data augmentation as means of improving malaria classification using convolutional neural network

• Main Authors: Abdullahi Muhammad, Fatima, Sudirman, Rubita, Ariffin, Ismail, Ramli, Norhafizah
• Format: Conference or Workshop Item
• Published: 2022
• Subjects: TK Electrical engineering. Electronics Nuclear engineering
• Online Access: http://eprints.utm.my/id/eprint/101443/; http://dx.doi.org/10.1109/IAICT55358.2022.9887391

One of the major limiting factors of the application of deep learning in automating malaria diagnosis is the insufficiency of labeled data for network training which leads to overfitting of the model on training data. Network regularization and data augmentation are two major techniques employed dur...