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학술대회 A Study on the Composition of Image-Based Ship-type/class Identification System
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저자
이지원, 남도원, 이정수, 문성원, 오아름, 유원영
발행일
202002
출처
International Conference on Advanced Communications Technology (ICACT) 2020, pp.203-206
DOI
https://dx.doi.org/10.23919/ICACT48636.2020.9061395
협약과제
19HS6700, 영상 내 객체간 관계 분석 기반 해상 선박/구조물 상세 식별 콘텐츠 기술 개발, 남도원
초록
Ships, coastal posts, and control centers need to verify the information, location, and speed of nearby vessels for various purposes, such as traffic control or maritime warfare. In the field of defense where accurate information on nearby ships is important, radar is used to acquire location information on nearby ships. However, the selection of the opponent's position as well as the high-value units must be more important and prioritized, and image-based warship type/class identification techniques are required in naval warfare. This paper presents a detailed method for system construction that supports detailed identification of warship type/class through structural analysis. Through the development of the proposed system, reliable warship identification can be used for tactical applications in the defense field, thereby contributing to the enhancement of defense capabilities.
키워드
Deep learning, Pattern matching, Ship classification, Structural analysis, Warship identification
KSP 제안 키워드
Detailed method, High-value, Identification system, Identification techniques, Image-based, Location information(GPS), Ship classification, Structural Analysis, System Construction, Traffic control, control center