항공영상을 이용한 딥러닝 기반 건물객체 추출 기법들의 비교평가

목차 (Table of Contents)

• Abstract
• 초록
• 1. 서론
• 2. 연구 방법
• 3. 연구 대상지 및 평가 방법
• 4. 실험 결과 및 분석
• 5. 결론
• References

참고문헌 (Reference)

1 서홍덕, "포인트 클라우드에서 딥러닝을 이용한 객체 분류 및 변화 탐지" 한국국토정보공사 50 (50): 37-51, 2020

2 이대건, "딥러닝을 위한 영역기반 합성곱 신경망에 의한 항공영상에서 건물탐지 평가" 한국측량학회 36 (36): 469-481, 2018

3 주기훈, "기계학습 옵티마이저 성능 평가" 한국전기전자학회 24 (24): 766-776, 2020

4 김혜진, "UAV 영상을 이용한 객체기반 건물 추출에 관한 연구" 대한공간정보학회 27 (27): 21-28, 2019

5 Ronneberger, O., "U-net:Convolutional networksfor biomedical image segmentation" 234-241, 2015

6 Jégou, S., "The one hundred layers tiramisu: Fully convolutional densenets for semantic segmentation" 1175-1183, 2017

7 Badrinarayanan, V., "SegNet: A deep convolutional encoder-decoder architecture for image segmentation" 39 (39): 2481-2495, 2017

8 Pashaei, M., "Review and evaluation of deep learning architectures for efficient land cover mapping with UAS hyper-spatial imagery : a case study over a wetland" 12 (12): 959-, 2020

9 Cheng, Z., "Remote sensing image segmentation method based on HRNet" 6750-6753, 2020

10 Huang, G., "Densely connected convolutional networks" 2261-2269, 2017

11 Sun, K., "Deep highresolution representation learning for human pose estimation" 5686-5696, 2019

12 Wang, J., "Deep high-resolution representation learning for visual recognition" 1-, 2020

13 Xu, Y., "Building extraction in very high resolution remote sensing imagery using deep learning and guided filters" 10 (10): 144-, 2018

14 Chen, D. Y., "Building extraction and number statistics in WUI areas based on UNet structure and ensemble learning" 13 (13): 1172-, 2021

15 Seo, K. H., "An empirical study on automatic building extraction from aerial images using a deep learning algorithm" 2019 (2019): 243-252, 2019

16 Zhang, L., "An efficient building extraction method from high spatial resolution remote sensing images based on improved Mask R-CNN" 20 (20): 1465-, 2020