Hybrid sigmoid activation function and transfer learning assisted breast cancer classification on histopathological images
Author:
Publisher
Springer Science and Business Media LLC
Subject
Computer Networks and Communications,Hardware and Architecture,Media Technology,Software
Link
https://link.springer.com/content/pdf/10.1007/s11042-023-17808-2.pdf
Reference36 articles.
1. Zheng J, Lin D, Gao Z, Wang S, He M, Fan J (2020) Deep learning assisted efficient AdaBoost algorithm for breast cancer detection and early diagnosis. IEEE Access 8:96946–96954
2. American Cancer Society. “www.cancer.org/treatment/understanding-your-diagnosis/what-is-cancer.” 14th Feb 2022
3. Yadavendra, Chand S (2020) A comparative study of breast cancer tumor classification by classical machine learning methods and deep learning method. Mach Vis Appl 31(6):46
4. Sharma S, Mehra R (2020) Effect of layer-wise fine-tuning in magnification-dependent classification of breast cancer histopathological image. Vis Comput 36:1755–1769
5. World Health Organization, “Global breast cancer initiative implementation framework: assessing, strengthening and scaling up of services for the early detection and management of breast cancer (who.int).” 7th March 2023
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