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Extended Siamese Convolutional Neural Networks for Discriminative Feature Learning
저자
Lee S.,Hong S.
학술지명
International Journal of Fuzzy Logic and Intelligent Systems
출판/발행연도
2022
주제
요약
본 연구에서는 기존 시암 컨볼루션 신경망(SCNN)의 한계를 극복하기 위해 독립적 특징과 상대적 특징을 모두 학습하는 확장 시암 컨볼루션 신경망(ESCNN)을 제안합니다. 제안하는 ESCNN은 다단계 특징을 활용하는 특징 증강 구조를 가지며, 사람 검증 문제에 적용한 결과 97.7%의 정확도를 달성하여 기존 SCNN 모델보다 성능이 향상됨을 확인했습니다.
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