On pig farms, the highest mortality rate is observed among nursing piglets. To reduce this mortality rate, farmers need to carefully observe the piglets to prevent accidents such as being crushed and to maintain a proper body temperature. However, observing a large number of pigs individually can be challenging for farmers. Therefore, our aim was to detect the behavior of piglets and sows in real-time using deep learning models, such as YOLOv4-CSP and YOLOv7-E6E, that allow for real-time object detection. YOLOv4-CSP reduces computational cost by partitioning feature maps and utilizing Cross-stage Hierarchy to remove redundant gradient calculation. YOLOv7-E6E analyzes and controls gradient paths such that the weights of each layer learn diverse features. We detected standing, sitting, and lying behaviors in sows and lactating and starving behaviors in piglets, which indicate nursing behavior and movement to colder areas away from the group. We optimized the model parameters for the best object detection and improved reliability by acquiring data through experts. We conducted object detection for the five different behaviors. The YOLOv4-CSP model achieved an accuracy of 0.63 and mAP of 0.662, whereas the YOLOv7-E6E model showed an accuracy of 0.65 and mAP of 0.637. Therefore, based on mAP, which includes both class and localization performance, YOLOv4-CSP showed the superior performance. Such research is anticipated to be effectively utilized for the behavioral analysis of fattening pigs and in preventing piglet crushing in the future.

Ⅰ. 서론
Ⅱ. 재료 및 방법
    1. 데이터셋 수집
    2. 데이터셋 제작
    3. 실시간 객체 탐지 딥러닝 모델
Ⅲ. 결과
    1. 성능평가 지표
    2. 성능 비교
Ⅳ. 고찰
사사
Ⅴ. 요약

• 이지현(강원대학교 BIT의료융합학과 대학원생) | Ji-hyeon Lee (Graduate Student, Dept. of Interdisciplinary Graduate Program for BIT Medical Convergence, Kangwon National University, Chuncheon 24341, Korea)
• 이한성(강원대학교 BIT의료융합학과 대학원생) | Han-sung Lee (Graduate Student, Dept. of Interdisciplinary Graduate Program for BIT Medical Convergence, Kangwon National University, Chuncheon 24341, Korea)
• 김진수(강원대학교 동물산업융합학과 교수) | Jin-Soo Kim (Professor, Dept. of Animal Industry Convergence, Kangwon National University, Chuncheon 24341, Korea)
• 최요한(국립축산과학원 연구원) | Yo Han Choi (Researcher, Swine Science Division, National Institute of Animal Science, Rural Development Administration, Cheonan 31000, Korea)
• 홍준선(국립축산과학원 연구원) | Jun Seon Hong (Researcher, Swine Science Division, National Institute of Animal Science, Rural Development Administration, Cheonan 31000, Korea)
• 박현주(국립축산과학원 연구원) | Hyun Ju Park (Researcher, Swine Science Division, National Institute of Animal Science, Rural Development Administration, Cheonan 31000, Korea)
• 조현종(강원대학교 IT대학 전자공학과 및 BIT의료융합학과 교수) | Hyun-chong Cho (Professor, Dept. of Electronics Engineering & Dept. of Interdisciplinary Graduate Program for BIT Medical Convergence, Kangwon National University, Chuncheon 24341, Korea) Corresponding author