1. Atila, U., Yusuf Yargı, B., Sehirli, E., Turan, M.K.: Classification of dna damages on segmented comet assay images using convolutional neural network. Comput. Methods Programs Biomed. 186, 105192 (2020)
2. Fairbairn, D.W., Olive, P.L., O’Neill, K.L.: The comet assay: a comprehensive review. Mutat. Res./Rev. Genet. Toxicol. 339(1), 37–59 (1995)
3. Glorot, X., Bengio, Y.: Understanding the difficulty of training deep feedforward neural networks. In: Proceedings of the 13th International Conference on Artificial Intelligence and Statistics (AISTATS), pp. 249–256. Sardinia, Italy (2010)
4. Gyori, B.M., Venkatachalam, G., Thiagarajan, P., Hsu, D., Clement, M.V.: OpenComet: an automated tool for comet assay image analysis. Redox Biol. 2(1), 457–465 (2014)
5. Hafiyan, Y.T., Yanuaryska, R.D., Anarossi, E., Sutanto, V.M., Triyanto, J., Sakakibara, Y.: A hybrid convolutional neural network-extreme learning machine with augmented dataset for DNA damage classification using comet assay from buccal mucosa sample. Int. J. Innovative Comput. Inf. Control 17(4), 1191–11201 (2021)