참고문헌 (20)

1. Hyun-Ju Choi, Tae-Yun Kim, Patrik Malm, Ewert Bengtsson, Heung-Kook Choi. Study on evaluating the significance of 3D nuclear texture features for diagnosis of cervical cancer. Korean Society of Computer Information. 2011;16(10):83-86. 

2. http://www.amc.seoul.kr/asan/healthinfo/disease/diseaseDetail.do?contentId31818, accessed on 2014. 

3. https://www.cancer.go.kr/lay1/program/S1T211C223/cancer/view.do?cancer_seq4877, accessed on Nov. 17, 2019. 

4. Alyafeai Z, Ghouti L. A fully-automated deep learning pipeline for cervical cancer classification. Expert Systems with Applications. 2020;83-86 

5. Chandran V, Sumithra MG, Karthick A, George T, Deivakani M, Elakkiya B, Subramaniam U, Manoharan S. Diagnosis of Cervical Cancer based on Ensemble Deep Learning Network using Colposcopy Images. BioMed Research International. 2021;83-86 

6. Yu Jin Seol, Young Jae Kim, Kye Hyun Nam, Kwang Gi Kim. Comparison on the Deep Learning Performance of a Field of View. Journal of Korea Multimedia Society. 2020;23(7):812-818. 

   원문보기 상세보기

7. Fei Jiang, Yong Jiang, Hui Zhi, Yi Dong, Hao Li, Sufeng Ma, Yilong Wang, Qiang Dong, Haipeng Shen, Yongjun Wang. Artificial intelligence in healthcare: past, present and future. Stroke Vasc Neurol. 2017;2(4):230-243. 

   상세보기

8. Youngtak Cho, Kiok Ahn. Design and Implementation of Automated Detection System of Personal Identification Information for Surgical Video De-Identification. Journal of convergence security. 2019;19(5):75-84. 

9. Korean society of Obstetrics and Gynecology (https://www.ksog.org/public/index.php?sub4&third4). 

10. http://www.samsunghospital.com/home/healthInfo/content/contentList.do?CONT_CLS_CD001020001&STDIS&TABDIS_NM&SW%EC%9E%90%EA%B6%81%EA%B2%BD%EB%B6%80%EC%95%94, accessed on 2015. 

11. Song E-H, Kim J-J, Myung N-H, Park C-H. Spiral Brush in PapSure Test for Cervical Cancer Screening. Korean Journal of Gynecologic Oncology and Colposcopy. 2002;13(4):313-326. 

    상세보기

12. Hee HS, Chern YJ, Classify And Visualize The Fatty Liver Using Class Activation Maps And CNN, Korea Institute Of Communication Sciences, 2020;18(10):83-86. 

13. Bolei Zhou, Aditya Khosla, Agata Lapedriza, Aude Oliva, Antonio Torralba. Learning Deep Features for Discriminative Localization. Computer Vision and Pattern Recognition. 2016;2921-2929. 

14. https://acsjournals.onlinelibrary.wiley.com/doi/full/10.3322/caac.21628, accessed on Jul. 30, 2020. 

15. Sangchul Kim, J. Nang. An Analysis of Luminance Histogram and Correlation of Motion Vector for Unsuitable Frames for Frame Rate Up Conversion. Korean Institute of Information Scientists and Engineers. 2016;22(10):532-536. 

16. Raghav Bansal, Gaurav Raj, Tanupriya Choudhury. Blur image detection using Laplacian operator and Open-CV. IEEE. 2017. 

17. Wang J, Song Y, Leung T, Rosenberg C, Wang J, Philbin J, Chen B, Wu Y. Learning Fine-grained Image Similarity with Deep Ranking. IEEE. 2014:1,386-1,393 

18. Kim MK. Feature Extraction on a Periocular Region and Person Authentication Using a ResNet Model. Journal of Korea Multimedia Society. 2019;22(12):1,347-1,355. 

19. Kang H-J. Efficient Fixed-Point Representation for ResNet50 Convolutional Neural Network. Journal of the Korea Institute of Information and Communication Engineering. 2018;22(1):1-8. 

    원문보기 상세보기

20. Jeon S-S, Son K-Y, Lee J-H, Oh J-S, Son S-H. A Comparison Analysis on the Sales Price of Apartments according to G-SEED by Using T-test. Journal of the Autumn Academic Presentation Conference. 2019;19(2):207-208. 

저자의 다른 논문 :

김영재 (14) 김광기 (53)