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.
피인용 0
초록·키워드
In fish farms, the overuse of feed can lead to residue and fish excrement polluting the water quality environment, thereby increasing the probability of pathogen proliferation and disease incidence in fish. In order to minimize the occurrence of diseases, it is crucial to administer an appropriate amount of feed and manage breeding diligently while mitigating any stress factors affecting the fish. This study involves the development of a fish species and disease detection system, where models are trained to identify different types of fish and their diseases. The system is designed to be used by fish farmers, offering a user-friendly interface through the Web. In the model training, the YOLOv7 model demonstrated high performance, achieving over 0.9 accuracy in detecting fish species. Meanwhile, for fish disease detection, the YOLOv5l model exhibited overall superior performance. However, there was a limitation in the dataset for fish disease detection, with only a small number of samples available. To overcome this, the fish species and disease detection system, developed in conjunction with the YOLOv5l model, was incorporated into the web page. This system aims to help identify the species, disease status, and specific affected regions in the fish population.
본문·목차
인공지능 문자 인식 모델을 통해 추출된 텍스트로, 일부 오타나 오류가 포함될 수 있으나 지속적으로 개선 중입니다.
오류를 발견하셨다면 해당 부분을 드래그한 후 ' 를 통해 신고해주세요.
오류를 발견하셨다면 해당 부분을 드래그한 후 ' 를 통해 신고해주세요.
최근 본 자료 전체보기
UCI(KEPA) : I410-ECN-0102-2023-004-002035572
