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Improving Chili Pepper Seed Germination Rates through Deep Learning Using Macroscopic Images

원문정보

Soo-Kyung Moon, Changyu-Ao, Seung-Eon Jeong, Dae-Won Park, Youn-Mo Soung, Man-Sung Kwen, Uk Cho, Dae-In Kang, Sung-Ho Jung, Gwang-Jun Kim

한국컴퓨터게임학회 한국컴퓨터게임학회논문지 제38권 제1호 2025.03 pp.106-115
피인용수 : 0건 (자료제공 : 네이버학술정보)

초록

영어

Germination of chili pepper seeds is critical for crop yield and resource utilization. A high germination rate increases yield and effectively reduces resource wastage. This study collected 450 macroscopic images of chili pepper seeds and constructed a dataset for deep learning training through standardized germination experiments. Six deep learning models were evaluated to improve the chili pepper seed classification accuracy and germination rate. After comparing the performance of the models, MobileNet_v2 performed the best, not only having the fewest number of parameters but also achieving a 98.89% accuracy and 97.82% F1 score. The model improved the original germination rate from 87.33% to 100% on the test set, significantly optimizing the seed selection process

목차

ABSTRACT
1. Introduction
2. Related Work
3. Materials and Methods
4. Results and Discussion
5. Conclusion And Future Work
참고문헌

키워드

저자정보

  • Soo-Kyung Moon Department of Computer Engineering, Chonnam National University, Yeosu, Seoul, Korea
  • Changyu-Ao Department of Computer Engineering, Chonnam National University, Yeosu, Seoul, Korea
  • Seung-Eon Jeong Department of Computer Engineering, Chonnam National University, Yeosu, Seoul, Korea
  • Dae-Won Park Department of Computer Engineering, Chonnam National University, Yeosu, Seoul, Korea
  • Youn-Mo Soung Department of Computer Engineering, Chonnam National University, Yeosu, Seoul, Korea
  • Man-Sung Kwen Department of Computer Engineering, Chonnam National University, Yeosu, Seoul, Korea
  • Uk Cho Department of Computer Engineering, Chonnam National University, Yeosu, Seoul, Korea
  • Dae-In Kang Department of Computer Engineering, Chonnam National University, Yeosu, Seoul, Korea
  • Sung-Ho Jung Department of Computer Engineering, Chonnam National University, Yeosu, Seoul, Korea
  • Gwang-Jun Kim Department of Computer Engineering, Chonnam National University, Yeosu, Seoul, Korea

참고문헌

자료제공 : 네이버학술정보

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