과제정보
This work was supported by the National Research Foundation of Korea (NRF) grant funded by the Korea government (MSIT) (NRF-2021R1F1A1049467) and by Korea National University of Transportation in 2023.
참고문헌
- Y. Ouyang, et al., "Classification of Benign and Malignant Breast Tumors Using H-Scan Ultrasound Imaging," Diagnostics (Basel), Vol. 8, 2019. DOI:https://doi:10.3390/diagnostics9040182.
- S. Han, et al., "A Weak and Semi-supervised Segmentation Method for Prostate Cancer in TRUS Images," Journal of Digital Imaging, Vol. 33, 2020. DOI:https://doi.org/10.1007/s10278-020-00323-3
- L. Shen, et al., "Deep Learning to Improve Breast Cancer Detection on Screening Mammography," Scientific Reports, Vol. 9, 2019. DOI:https://doi.org/10.1038/s41598-019-48995-4
- S. Han, et al, "A Practical Implementation of Deep Learning Method for Supporting the Classification of Breast Lesions in Ultrasound Images," International Journal of Advanced Smart Convergence Vol.8 , pp. 24-34, 2019. DOI:https://doi.org/10.7236/IJASC.2019.8.1.24
- Y. Gu, et al., "Deep learning based on ultrasound images assists breast lesion diagnosis in China: a multicenter diagnostic study," Insights into Imaging, Vol. 13, 2022. DOI:https://doi.org/10.1186/s13244-022-01259-8
- X. Yang, et al, "A Survey on Deep Semi-Supervised Learning," IEEE Transactions on Knowledge and Data Engineering, Vol. 35, 2022. DOI:https://doi.org/10.1109/TKDE.2022.3220219
- E. Arazo, et al, "Pseudo-Labeling and Confirmation Bias in Deep Semi-Supervised Learning," proceedings of International Joint Conference on Neural Networks (IJCNN), 2020. DOI:https://doi.org/10.1109/IJCNN48605.2020.9207304.
- Y. Chen, et al, "Semi-Supervised Learning under Class Distribution Mismatch," Proceedings of the AAAI Conference on Artificial Intelligence, 2020. DOI:https://doi.org/10.1609/aaai.v34i04.5763
- S. Lee, S. Han, "Detection Fastener Defect using Semi Supervised Learning and Transfer Learning," Journal of Internet Computing and Services, Vol. 24, 2023. DOI:https://doi.org/ 10.7472/jksii.2023.24.6.91
- W. Al-Dhabyan,et al, "Dataset of breast ultrasound images," Data in Brief, Vol. 28, 2020. DOI:https://doi.org/10.1016/j.dib.2019.104863
- K. He, X. Zhang, S. Ren and J. Sun, "Deep Residual Learning for Image Recognition," 2016 IEEE Conference on Computer Vision and Pattern Recognition, pp.770-778, 2016. DOI:https://doi.org/10.1109/CVPR.2016.90
- S. Lee, and S, Han, "Detection Fastener Defect using Semi Supervised Learning and Transfer Learning," J. Internet Comput. Serv., Vol. 24, pp. 91-98, 2023. DOI: http://dx.doi.org/10.14801/jkiit.2022.20.2.
- T. Chen, K. Simon, N. Mohammad and G. Hinton, "A Simple Framework for Contrastive Learning of Visual Representations," In International conference on machine learning, pp.1597-1607, 2020. DOI:https://arxiv.org/abs/2002.05709.
- X. Wang, G. Qi, "Contrastive Learning With Stronger Augmentations," IEEE Transactions on Pattern Analysis and Machine Intelligence, Vol. 45, pp..21271-21284, 2022. DOI:https://doi.org/10.1109/TPAMI.2022.3203630