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논문 기본 정보

자료유형
학술저널
저자정보
Jeyoung Lee (Department of Digital Media, The Catholic University of Korea) Hochul Kang (Department of Digital Media, The Catholic University of Korea)
저널정보
한국축산학회(구 한국동물자원과학회) 한국축산학회지 Journal of Animal Science and Technology Vol.66 No.4
발행연도
2024.7
수록면
846 - 858 (13page)

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In a duck cage, ducks are placed in various states. In particular, if a duck is overturned and falls or dies, it will adversely affect the growing environment. In order to prevent the foregoing, it was necessary to continuously manage the cage for duck growth. This study proposes a method using an object detection algorithm to improve the foregoing. Object detection refers to the work to perform classification and localization of all objects present in the image when an input image is given. To use an object detection algorithm in a duck cage, data to be used for learning should be made and the data should be augmented to secure enough data to learn from. In addition, the time required for object detection and the accuracy of object detection are important. The study collected, processed, and augmented image data for a total of two years in 2021 and 2022 from the duck cage. Based on the objects that must be detected, the data collected as such were divided at a ratio of 9 : 1, and learning and verification were performed. The final results were visually confirmed using images different from the images used for learning. The proposed method is expected to be used for minimizing human resources in the growing process in duck cages and making the duck cages into smart farms.

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