http://chineseinput.net/에서 pinyin(병음)방식으로 중국어를 변환할 수 있습니다.
변환된 중국어를 복사하여 사용하시면 됩니다.
K-겹 교차 검증과 서포트 벡터 머신을 이용한 고무 오링 결함 검출 시스템
이용은(Yong Eun Lee),최낙준(Nak Joon Choi),변영후(Young Hoo Byun),김대원(Dae Won Kim),김경천(Kyung Chun Kim) 한국가시화정보학회 2021 한국가시화정보학회지 Vol.19 No.1
In this study, the detection of rubber o-ring defects was carried out using k-fold cross validation and Support Vector Machine (SVM) algorithm. The data process was carried out in 3 steps. First, we proceeded with a frame alignment to eliminate unnecessary regions in the learning and secondly, we applied gray-scale changes for computational reduction. Finally, data processing was carried out using image augmentation to prevent data overfitting. After processing data, SVM algorithm was used to obtain normal and defect detection accuracy. In addition, we applied the SVM algorithm through the k-fold cross validation method to compare the classification accuracy. As a result, we obtain results that show better performance by applying the k-fold cross validation method.