Infield Honeysuckle Detection Based on Improved YOLOv5s Under Natural Lighting
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Publisher
Springer Nature Singapore
Link
https://link.springer.com/content/pdf/10.1007/978-981-97-6441-9_6
Reference34 articles.
1. Yan K, Cui M, Zhao S, Chen X, Tang X (2016) Salinity stress is beneficial to the accumulation of chlorogenic acids in honeysuckle (Lonicera japonica Thunb.). Front Plant Sci 7. https://doi.org/10.3389/fpls.2016.01563
2. Zhang X, Li Y, Yue C, Liu X (2023) Green and efficient cultivation techniques for honeysuckle. Seed Sci Technol 41, 49–51+66. https://doi.org/10.19904/j.cnki.cn14-1160/s.2023.24.016
3. Li X (2022) Cultivation techniques and development models of honeysuckle in Xingtai, Hebei province. Agric Eng Technol 42, 80+82. https://doi.org/10.16815/j.cnki.11-5436/s.2022.05.050
4. Liu X, Zhang Z, Igathinathane C, Flores P, Zhang M, Li H, Han X, Ha T, Ampatzidis Y, Kim H-J (2024) Infield corn kernel detection using image processing, machine learning, and deep learning methodologies under natural lighting. Expert Syst Appl 238:122278. https://doi.org/10.1016/j.eswa.2023.122278
5. Zheng R, Sun Q, Xiao G (2022) Research on honeysuckle image recognition processing algorithm based on machine vision. J Chin Agric Mech 43, 153–159. https://doi.org/10.13733/j.jcam.issn.2095-5553.2022.04.022
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