인문학
사회과학
자연과학
공학
의약학
농수해양학
예술체육학
복합학
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.
초록·키워드
This study proposes a 6-degree-of-freedom (DOF) active re-observation method for detecting strawberry disease symptoms hidden from a single front view. The experimental evaluation was conducted using 50 mock strawberries, which were reused across 10 randomized trials. After grasping a fruit, the manipulator reorients it toward a red, green, blue plus depth (RGB-D) camera for backside inspection, supported by the small-sized You Only Look Once version 8 segmentation model, 18-layer residual network, RGB-D localization, and principal component analysis (PCA)-based roll estimation. In 200 trials per structure, backside simulated-lesion detection success rates were 64.50±11.65% with 4 DOF and 94.00±4.59% with 6 DOF. Across 10 repeated evaluations totaling 500 trials, 187 of 200 backside-only simulated-disease cases were detected, and 284 of 300 simulated-disease-condition trials were successfully identified and sorted (94.67±3.91%). A representative 50-target evaluation required approximately 18 min, corresponding to 21.6 s per target and 166.7 targets/h under the specified laboratory test composition condition; the displayed online processing rate ranged from 13.6 to 15.0 frames per second. These results demonstrate feasibility under controlled laboratory conditions, while greenhouse performance and damage to real fruit remain to be evaluated.
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.