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논문검색

THE KOREAN SOCIETY OF FORENSIC SCIENCES

HOME 학회지 논문검색
pISSN: 1598-0715

한국법과학회지, Vol.23 no.2 (2022)
pp.30~39

DOI : 10.53051/ksfs.2022.23.2.004

- 합성곱 신경망 기반 STR 전기영동 이미지를 이용한 DNA 프로필 인식 및 예측 -

박현철

(국립과학수사연구원 유전자과 감정관)

안으리

(대구과학수사연구소 유전자분석과 감정관)

The convolutional neural network (CNN) is a deep learning method to recognize images with high accuracy and low error rate. In this study, we performed classification of DNA profiles based on electropherogram images using the CNN. 1,800 DNA profiles images of three control DNAs (007, 2800M, 9947A) were used for CNN model as a dataset. A dataset was divided into the train and test data set, and 1,500 and 300 images were used, respectively. The CNN model used the LeNet-5 architecture, and an accuracy of model was estimated by k-fold cross validation. Both the training data set and test data set showed an accuracy of 1.0 and a loss rate of 0 with 50 epochs. All 300 images of test data set exactly matched the actual data, and the predict probability of match for each element showed 0.579.

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