지원사업
학술연구/단체지원/교육 등 연구자 활동을 지속하도록 DBpia가 지원하고 있어요.
커뮤니티
연구자들이 자신의 연구와 전문성을 널리 알리고, 새로운 협력의 기회를 만들 수 있는 네트워킹 공간이에요.
논문 기본 정보
- 자료유형
- 학술저널
- 저자정보
- 발행연도
- 2024.3
- 수록면
- 424 - 434 (11page)
- DOI
- 10.7840/kics.2024.49.3.424
이용수
초록· 키워드
오류제보하기
In this paper, a method is proposed to perform consistent detection of small objects across all altitudes using UAVs. Unlike traditional tiling algorithms that detect small objects with a fixed number of tiles, our method dynamically adjusts the number of tiles based on the altitude and the size of the bounding box. This approach determines the proper number of tiles for detecting small objects at each altitude. Real-time object detection was conducted on the AI board mounted on the UAV, and for this purpose, the model was optimized using a lightweighting process. Using the Visdrone dataset, the performance of small object detection at each altitude was tested in real-world conditions. Compared to the conventional YOLOv5 and fixed-number tiling algorithms, our method consistently detected small objects at all altitudes.
목차
ABSTRACT
Ⅰ. Introduction
Ⅱ. Real-time Automatic Tiling
Ⅲ. Experiment
Ⅳ. Conclusions
References
참고문헌 (30)
참고문헌 신청
D. Forsyth and J. Ponce, Computer Vision: A Modern Approach, Prentice Hall, 2011.
A. Voulodimos, N. Doulamis, A. Doulamis, and E. Protopapadakis, “Deep learning for computer vision: A brief review,” Computational Intell. and Neurosci., vol. 2018, no. Article ID 7068349, pp. 1-13, Feb. 2018. (https://doi.org/10.1155/2018/7068349)
L. Liu, W. Ouyang, X. Wang, et al., “Deep learning for generic object detection: A survey,” Int. J. Comput. Vis., vol. 128, no. 2, pp. 261-318, Oct. 2019. (https://doi.org/10.1007/s11263-019-01247-4)
B. Zhao, J. Feng, X. Wu, et al., “A survey on deep learning-based fine-grained object classification and semantic segmentation,” Int. J. Autom. Comput., vol. 14, no. 2, pp. 119-135, Jan. 2017. (https://doi.org/10.1007/s11633-017-1053-3)
Z. Zou, K. Chen, Z. Shi, Y. Guo, and J. Ye, “Object detection in 20 years: A survey,” in Proc. IEEE, vol. 111, no. 3, pp. 257-276, Mar. 2023. (https://doi.org/10.1109/JPROC.2023.3238524)
A. Voulodimos, N. Doulamis, A. Doulamis, and E. Protopapadakis, “Deep learning for computer vision: A brief review,” Computational Intell. and Neurosci., vol. 2018, no. Article ID 7068349, pp. 1-13, Feb. 2018. (https://doi.org/10.1155/2018/7068349)
L. Liu, W. Ouyang, X. Wang, et al., “Deep learning for generic object detection: A survey,” Int. J. Comput. Vis., vol. 128, no. 2, pp. 261-318, Oct. 2019. (https://doi.org/10.1007/s11263-019-01247-4)
B. Zhao, J. Feng, X. Wu, et al., “A survey on deep learning-based fine-grained object classification and semantic segmentation,” Int. J. Autom. Comput., vol. 14, no. 2, pp. 119-135, Jan. 2017. (https://doi.org/10.1007/s11633-017-1053-3)
Z. Zou, K. Chen, Z. Shi, Y. Guo, and J. Ye, “Object detection in 20 years: A survey,” in Proc. IEEE, vol. 111, no. 3, pp. 257-276, Mar. 2023. (https://doi.org/10.1109/JPROC.2023.3238524)
이 논문의 저자 정보
이 논문과 함께 이용한 논문
차량 탑재형 상·하역 장비의 설계와 딥러닝 객체 인식을 이용한 자동제어 방법
이순교
,
김선목
,
우효원
외 2명
로봇학회 논문지
2024
.03
YOLOv8n에서 2인 탑승 전동 킥보드 탐지 개선을 위한 새로운 라벨링 방법 제안
남궁동혁
,
김동회
디지털콘텐츠학회논문지
2023
.07
Object Detection과 OCR을 활용한 다중 책 제목 검출 모델
김성연
,
박진우
,
김상민
외 2명
한국정보기술학회논문지
2023
.02
Mixed Reality-Based Indoor Navigation System in Multi-Story Environments
Eun Bee Kim
,
Soo Young Shin
한국통신학회논문지
2024
.08
Deep-Learning Based Missing Child Detection Assistance System Using Autonomous Robot
Yeong Eun Choi
,
Su Hyeon Kang
,
So Yeon Kim
외 1명
한국통신학회논문지
2024
.07
최근 본 자료
댓글(0)
0
UCI(KEPA) : I410-151-24-02-089492075