과제정보
본 연구는 2018년도 정부(교육부)의 재원으로 한국연구재단의 지원을 받아 수행되었음 (NO. NRF-2018R1A6A1A08025348). 본 연구는 국토교통부/국토교통과학기술진흥원의 지원으로 수행되었음(스마트건설기술개발 국가R&D사업 : 과제번호 21SMIP-A158708-02).
참고문헌
- 한국산업안전보건공단, 산업재해 현황 분석, 2014-2018.
- Wang, Qian, and Min-Koo Kim. "Applications of 3D point cloud data in the construction industry: A fifteen-year review from 2004 to 2018." Advanced Engineering Informatics 39 (2019): 306-319. https://doi.org/10.1016/j.aei.2019.02.007
- Devlin, Jacob, et al. "Bert: Pre-training of deep bidirectional transformers for language understanding." arXiv preprint arXiv:1810.04805 (2018).
- Reimers, Nils, and Iryna Gurevych. "Sentence-bert: Sentence embeddings using siamese bert-networks." arXiv preprint arXiv:1908.10084 (2019).
- Qi, Charles R., et al. "Pointnet: Deep learning on point sets for 3d classification and segmentation." Proceedings of the IEEE conference on computer vision and pattern recognition. 2017.
- Hu, Qingyong, et al. "RandLA-Net: Efficient semantic segmentation of large-scale point clouds." Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition. 2020.