참고문헌 (10)

1. Daeyoung Choi, et al., "A Study on Deep-Learning based Crack Analysis for Visual-safety Inspection of Bridge", Proceedings of KIIT Conference, Jeju, Korea, pp. 1-3, Jun. 2021. 

2. Kim, H., Ahn, E., Cho, S., Shin, M., Sim, S.H.. Comparative analysis of image binarization methods for crack identification in concrete structures. Cement and concrete research, vol.99, 53-61.

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3. 10.1109/CVPR.2015.7298965 Jonathan Long, Evan Shelhamer, and Trevor Darrell, "Fully convolutional networks for semantic segmentation", Proc. of the IEEE conference on computer vision and pattern recognition, Boston, MA, USA, pp. 3431-3440, Jun. 2015. https:// doi.org/10.1109/CVPR. 2015.7298965. 

   

4. 10.1007/978-3-319-24574-4_28 

   

5. Paik, Seung Hyun, Choi, Daeyoung, Kim, Young-Kyu, Jung, SangWoo, Kim, Dae-Nyeon. Implementation of the Drones with Deep-Learning Crack Detection Analysis for Inspection of Bridge. 韓國情報技術學會論文誌 = Journal of Korean institute of information technology, vol.19, no.3, 45-52.

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6. Ozgenel, Calar Fırat, "Concrete Crack Segmentation Dataset", Mendeley Data, Vol. 1, Apr. 2019. http://dx.doi.org/10.17632/jwsn7tfbrp.1. 

7. 10.1109/CVPR.2019.00075 

   

8. Nishikawa, Takafumi, Yoshida, Junji, Sugiyama, Toshiyuki, Fujino, Yozo. Concrete Crack Detection by Multiple Sequential Image Filtering. Computer-aided civil and infrastructure engineering, vol.27, no.1, 29-47.

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9. Weng, Xingxing, Huang, Yuchun, Wang, Wenzong. Segment-based pavement crack quantification. Automation in construction, vol.105, 102819-.

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10. Gehan, Malia A., Fahlgren, Noah, Abbasi, Arash, Berry, Jeffrey C., Callen, Steven T., Chavez, Leonardo, Doust, Andrew N., Feldman, Max J., Gilbert, Kerrigan B., Hodge, John G., Hoyer, J. Steen, Lin, Andy, Liu, Suxing, Lizárraga, César, Lorence, Argelia, Miller, Michael, Platon, Eric, Tessman, Monica, Sax, Tony. PlantCV v2: Image analysis software for high-throughput plant phenotyping. PeerJ, vol.5, e4088-.

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