인문학
사회과학
자연과학
공학
의약학
농수해양학
예술체육학
복합학
DBpia AI
AI 에이전트
AI 아이디어
AI 리더
AI 뷰어
Citeasy
크롬 서지관리 다운로드
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
- 학술대회자료
- 저자정보
- 발행연도
- 2024.1
- 수록면
- 211 - 219 (9page)
이용수
초록· 키워드
Heritage trees are highly valued and protected by national laws because of their cultural and historical significance. However, due to the financial and time constraints associated with the continuous monitoring of the heritage trees, unnecessary losses are reported annually. As a solution, this study suggests an artificial intelligence(AI)-based heritage tree disease diagnosis system on Zelkova serrata. We have compared several state-of-the-art deep learning models with transfer learning on the Zelkova Serrata Dataset which consists of 680 images. All models achieved outstanding classification results even only using pre-trained weights of ImageNet, with F1 scores ranging from 92.00% to 96.26%. Particularly when additionally leveraging the plant disease datasets, model performances improved to a range of 93.78% to 99.45%. Through this research, we proposed the concept of AI-based heritage tree disease diagnosis using transfer learning. This system is expected to reduce the aforementioned financial and time constraints.
상세정보 수정요청해당 페이지 내 제목·저자·목차·페이지정보가 잘못된 경우 알려주세요!
목차
- Abstract
- 1. Introduction
- 2. Heritage tree disease diagnosis dataset
- 3. Methods
- 4. Results
- 5. Discussion and Conclusion
- Reference
참고문헌
참고문헌 신청최근 본 자료
UCI(KEPA) : I410-151-24-02-089381460
