Author:
Wu Chien-Cheng,Hsu Chao-Hsiung,Wang Paul C.,Tu Tsang-Wei,Hsu Yi-Yu
Publisher
Springer Nature Switzerland
Reference20 articles.
1. Gharieb, R.R., Gendy, G., Abdelfattah, A.: C-means clustering fuzzified by two membership relative entropy functions approach incorporating local data information for noisy image segmentation. Sig. Image Video Process 11, 541–548 (2017). https://doi.org/10.1007/s11760-016-0992-4
2. Dubey, Y.K., Mushrif, M.M.: FCM clustering algorithms for segmentation of brain MR images. Adv. Fuzzy Syst. 2016(3), 1–14 (2016)
3. Bernard, O., Lalande, A., Zotti, C., et al.: Deep learning techniques for automatic MRI cardiac multi-structures segmentation and diagnosis: is the problem solved? IEEE Trans. Med. Imaging 37, 2514–2525 (2018). https://doi.org/10.1109/TMI.2018.2837502
4. Momeny, M., Neshat, A.A., Hussain, M.A., et al.: Learning-to-augment strategy using noisy and denoised data: improving generalizability of deep CNN for the detection of COVID-19 in X-ray images. Comput. Biol. Med. (2021). https://doi.org/10.1016/j.compbiomed.2021.104704
5. Akbiyik, M.E.: Data Augmentation in Training CNNs: Injecting Noise to Images (2023)