Detection and localization of citrus picking points based on binocular vision-Reference-Cited by-同舟云学术

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Detection and localization of citrus picking points based on binocular vision

Published:2024-07-28 Issue: Volume: Page:
ISSN:1385-2256
Container-title:Precision Agriculture
language:en
Short-container-title:Precision Agric

Author:

Hou Chaojun,Xu Jialiang,Tang Yu^ORCID,Zhuang Jiajun,Tan Zhiping,Chen Weilin,Wei Sheng,Huang Huasheng,Fang Mingwei

Funder

Natural Science Foundation of Guangdong Province

Innovation Team Project of Universities in Guangdong Province

Key Construction Discipline Research Capacity Enhancement Project of Guangdong Province

Young Talent Support Project of Guangzhou Association for Science and Technology

the Rural Revitalization Strategy Project of Guangdong Province

Publisher

Springer Science and Business Media LLC

Link

https://link.springer.com/content/pdf/10.1007/s11119-024-10169-2.pdf

Reference35 articles.

1. Bodla, N., Singh, B., Chellappa, R., & Davis, L. S. (2017). Soft-NMS–improving object detection with one line of code. IEEE International Conference on Computer Vision (ICCV), 2017, 5562–5570. https://doi.org/10.1109/iccv.2017.593

2. Briechle, K., & Hanebeck, U. D. (2001). Template matching using fast normalized cross correlation. Optical Pattern Recognition XII, 4387, 95–102. https://doi.org/10.1117/12.421129

3. Cai, Z., & Vasconcelos, N. (2021). Cascade R-CNN: High quality object detection and instance segmentation. IEEE Transactions on Pattern Analysis & Machine Intelligence, 43, 1483–1498. https://doi.org/10.1109/TPAMI.2019.2956516

4. Chen, Y., Wang, J., Zeng, Z., Zou, X., & Chen, M. (2019). Research on vision pre-positioning for litchi picking robot under large field of view. Transactions of the Chinese Society of Agricultural Engineering, 35, 48–54. https://doi.org/10.11975/j.issn.1002-6819.2019.23.006

5. Fang, H., Sun, J., Wang, R., Gou, M., Li, Y.-L., & Lu, C. (2019). InstaBoost: Boosting instance segmentation via probability map guided copy-pasting. IEEE/CVF International Conference on Computer Vision (ICCV), 2019, 682–691. https://doi.org/10.1109/ICCV.2019.00077

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