Scopus

A Comparative Study of Medical Preprocessing Techniques for Transfer Learning in Cervical Cytology Classification

Năm XB 2026 Tạp chí / Hội thảo Advances in Information and Communication Technology (ICTA 2025) Đơn vị ICTU DOI / Link https://doi.org/10.1007/978-3-032-18162-6_9 ↗

Tác giả

Tóm tắt

Accurate classification of cervical cytology images is essential for early detection of cervical cancer, particularly in low-resource clinical settings. While transfer learning has shown strong performance in medical image classification tasks [6, 8], the role of...

Tài liệu tham khảo

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[2] Ganaie, M.A., Hu, M., Malik, A.K., Tanveer, M., Suganthan, P.N.: Ensemble deep learning: a review. Eng. Appl. Artif. Intell. 115, 105151 (2022)

[3] He, K., Zhang, X., Ren, S., Sun, J.: Deep residual learning for image recognition. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR), pp. 770–778 (2016)

[4] Huang, G., Liu, Z., Van Der Maaten, L., Weinberger, K.Q.: Densely connected convolutional networks. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR), pp. 4700–4708 (2017)

[5] Kessler, T.A.: Cervical cancer: prevention and early detection. Semin. Oncol. Nurs. 33, 172–183 (2017)

[6] Litjens, G., et al.: A survey on deep learning in medical image analysis. Med. Image Anal. 42, 60–88 (2017)

[7] Szegedy, C., Vanhoucke, V., Ioffe, S., Shlens, J., Wojna, Z.: Rethinking the inception architecture for computer vision. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR), pp. 2818–2826 (2016)

[8] Zhao, Z., Alzubaidi, L., Zhang, J., Duan, Y., Gu, Y.: A comparison review of transfer learning and self-supervised learning: definitions, applications, advantages and limitations. Expert Syst. Appl. 242, 122807 (2024)

Ghi chú

Source ID: 47; Author classification: ICTU - Main Author; First listed author: Van-Khanh Tran1; Contact author: Van-Khanh Tran1; Total authors: 3; Not found in provided Springer books 10.1007/978-3-032-18159-6 or 10.1007/978-3-032-18316-3