1 |
Szeliski, R. (2010). Computer vision: algorithms and applications. Springer Science & Business Media.
|
2 |
Jo, H. J., Kim, Dawit., & Song, J. B. (2019). Automatic Dataset Generation of Object Detection and Instance Segmentation using Mask R-CNN. Journal of Korea Robotics Society, 14(1), 31-39.
DOI
|
3 |
Seo, K. H., Oh, C. H., Kim, David., Lee, M. Y., & Yang, Y. J. (2019). An empirical study on automatic building extraction from aerial images using a deep learning algorithm. Proceedings of Korean Society for Geospatial Information Science, Korea Spatial Information Society, 243-252.
|
4 |
Yoo, J. H., Lim, M. K., Ihm, C. H., Choi, E. S., & Kang, M. S., (2017). A Study on Prediction of Rheumatoid Arthritis Using Machine Learning. International Journal of Applied Engineering Research, 12(20), 9858-9862.
|
5 |
Na, Y. H., Kim, J. H., & Choi, J. P. (2019). Deep Learning Architecture for Building Extraction from Aerial Images. Proceedings of Symposium of the Korean Institute of communications and Information Sciences, Korea Institute of Communication Sciences, 396-397.
|
6 |
An, S. H., Yeo, S. H., & Kang, M. S. (2021). A Study on a car Insurance purchase Prediction Using Two-Class Logistic Regression and Two-Class Boosted Decision Tree. Korean Journal of Artificial Intelligence, 9(1), 9-14.
|
7 |
Choi, E. S., Yoo, H. J., Kang, M. S., & Kim, S. A. (2020). Applying Artificial Intelligence for Diagnostic Classification of Korean Autism Spectrum Disorder. Psychiatry investigation, 17(11), 1090-1095.
DOI
|
8 |
Forsyth, D., & Ponce, J. (2011). Computer vision: A modern approach. Prentice hall.
|
9 |
He, K., Gkioxari, G., Dollar, P., & Girshick, R. (2017). Mask r-cnn. In Proceedings of the IEEE international conference on computer vision, 2961-2969.
|
10 |
Jung, I. C., Kim, Y. S., Im, S. R., & Ihm, C. H., (2021). A Development of Nurse Scheduling Model Based on Q-Learning Algorithm. Korean Journal of Artificial Intelligence, 9(1), 1-7.
|
11 |
Lee, Y. S. (2017). Value Creation and Competitiveness Achievement Strategies of Smart Cities. Journal of the Korean Regional Science Association, 33(1), 59-68.
DOI
|
12 |
Kim, H. S. (2021). Mask R-CNN deep learning for fashion element detection. Journal of Digital Contents Society, 22(4), 689-696.
DOI
|
13 |
Kim, S. Y., Lee, H. H., Choi, E. S., & Go, J. U. (2020). A Case Study on the Construction of 3D Geo-spatial Information for Digital Twin Implementation. Journal of the Korean Association of Geographic Information Studies, 23(3), 146-160.
DOI
|
14 |
LeCun, Y., Bottou, L., Bengio, Y., & Haffner, P. (1998). Gradient-based learning applied to document recognition. Proceedings of the IEEE, 86(11), 2278-2324.
DOI
|
15 |
Mun, J. H., Jung, S. W., (2021). A customer credit Prediction Researched to Improve Credit Stability based on Artificial Intelligence. Korean Journal of Artificial Intelligence, 9(1), 21-27.
|
16 |
Park, Y. J. (2019). Strategy for Building Smart City as a Platform of the 4th Industrial Revolution. Journal of Digital Convergence, 17(1), 169-177.
DOI
|
17 |
Lee, W. Y., Ko, K. E., Kang, J. H., Park, H. J., & Jang, I. H. (2020). Instance Segmentation based Recognition System Tracking Tomatoes by Ripeness in Natural Light Condition. Journal of Institute of Control, Robotics and Systems, 26(11), 940-948.
DOI
|
18 |
Jeong, B. J., Zhang, Fan. (2017). A Study on the Emoticon Extraction based on Facial Expression Recognition using Deep Learning Technique. Korean Journal of Artificial Intelligence, 5(2), 43-53.
DOI
|
19 |
Kang, M. S., & Choi, E.S. (2021). MACHINE LEARNING: Concepts, Tools and Data Visualization. World Scientific.
|
20 |
Lee, I. S. (2021). A Study on Geospatial Information Role in Digital Twin. Journal of the Korea Academia-Industrial Cooperation Society, 22(3), 268-278.
DOI
|
21 |
Park, J. G., Choi, E. S., Kang, M. S., & Jung, Y. G. (2017). Dropout Genetics Algorithm Analysis for Deep Learning Generalization Error Minimization. International Journal of Advanced Culture Technology, 5(2), 74-81.
DOI
|
22 |
Rasheed, A., San, O. and Kvamsdal, T. 2020. Digital twin: Values, challenges and enablers from a modeling perspective. IEEE Access 8:21980-22012.
DOI
|