Dense object detection methods in RAW UAV imagery based on YOLOv8-Reference-Cited by-同舟云学术

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Dense object detection methods in RAW UAV imagery based on YOLOv8

Published:2024-08-04 Issue:1 Volume:14 Page:
ISSN:2045-2322
Container-title:Scientific Reports
language:en
Short-container-title:Sci Rep

Author:

Wu Zhenwei,Wang Xinfa,Jia Meng,Liu Minghao,Sun Chengxiu,Wu Chenyang,Wang Jianping

Funder

Key Science and Technology Program of Henan Province

Colleges and Universities Key Research Project of Henan Province

Key Science and Technology Program of Xinxiang City

Publisher

Springer Science and Business Media LLC

Link

https://www.nature.com/articles/s41598-024-69106-y.pdf

Reference74 articles.

1. Tang, Y., Zhou, H., Wang, H. & Zhang, Y. Fruit detection and positioning technology for a Camellia oleifera C. Abel orchard based on improved YOLOv4-tiny model and binocular stereo vision. Exp. Syst. Appl. 211, 118573. https://doi.org/10.1016/j.eswa.2022.118573 (2023).

2. Anders, M., Grass, I., Linden, V. M. G., Taylor, P. J. & Westphal, C. Smart orchard design improves crop pollination. J. Appl. Ecol. 60, 624–637. https://doi.org/10.1111/1365-2664.14363 (2023).

3. Liu, Q., Wang, X., Zhao, M. & Liu, T. Synergistic influence of the capture effect of western flower thrips (Frankliniella occidentalis) induced by proportional yellow-green light in the greenhouse. Int. J. Agric. Biol. Eng. 16, 88–94. https://doi.org/10.25165/j.ijabe.20231601.7562 (2023).

4. Aguilar-Ariza, A. et al. UAV-based individual Chinese cabbage weight prediction using multi-temporal data. Sci. Rep. 13, 20122. https://doi.org/10.1038/s41598-023-47431-y (2023).

5. Wang, X. et al. Lightweight SM-YOLOv5 tomato fruit detection algorithm for plant factory. Sensors 23, 3336. https://doi.org/10.3390/s23063336 (2023).

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