19PS1900, Development of original technology for artificial intelligence system for autonomous navigating ship ,
Moon Kyeong Deok
Abstract
최근 자율운항선박에 대한 관심이 증가하고 있으며, 바다를 항해하는 자율운항선박은 유인선과 같이국제해상충돌방지규칙을 준수해야한다. 따라서 본 논문에서는 자율운항선박이 국제해상충돌예방규칙을 준수하기위해서 필요한 선박 범주 및 합성곱 신경망 기반의 선박 분류 기술을 제안하였다. 먼저 국제해상충돌예방규칙을 분석하여자율운항선박이 구별해야 되는 14개의 선박 범주를 정의하였다. 또한 본 논문에서 정의된 선박 범주에 맞도록 인터넷 영상검색 및 기존 데이터 셋 정제를 통하여 40,300장 규모의 선박 범주 분류 데이터 셋을 구축하였다. 마지막으로 최신 합성곱신경망 모델을 구축된 선박 범주 분류 데이터 셋에 적용하여 선박 범주 분류 성능을 분석하였다. 실험결과 전이학습을통하여 학습된 Inception-ResNet v2 모델은 14개 선박 범주를 91%의 높은 정확도로 분류함을 확인하였다
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