Optimization strategies of fruit detection to overcome the challenge of unstructured background in field orchard environment: a review-Reference-Cited by-同舟云学术

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Optimization strategies of fruit detection to overcome the challenge of unstructured background in field orchard environment: a review

Published:2023-03-23 Issue:4 Volume:24 Page:1183-1219
ISSN:1385-2256
Container-title:Precision Agriculture
language:en
Short-container-title:Precision Agric

Author:

Tang Yunchao^ORCID,Qiu Jiajun,Zhang Yunqi,Wu Dongxiao,Cao Yuhong,Zhao Kexin,Zhu Lixue

Funder

key-area Research and Development Program of Guangdong Province

Science and Technology Planning Project of Guangzhou

Publisher

Springer Science and Business Media LLC

Subject

General Agricultural and Biological Sciences

Link

https://link.springer.com/content/pdf/10.1007/s11119-023-10009-9.pdf

Reference166 articles.

1. Apolo-Apolo, O. E., Martínez-Guanter, J., Egea, G., Raja, P., & Pérez-Ruiz, M. (2020a). Deep learning techniques for estimation of the yield and size of citrus fruits using a UAV. European Journal of Agronomy, 115, 126030. https://doi.org/10.1016/j.eja.2020.126030

2. Apolo-Apolo, O. E., Pérez-Ruiz, M., Martínez-Guanter, J., & Valente, J. (2020b). A cloud-based environment for generating yield estimation maps from apple orchards using UAV imagery and a deep learning technique. Frontiers in Plant Science, 11, 1086. https://doi.org/10.3389/fpls.2020.01086

3. Aquino, A., Millan, B., Diago, M., & Tardaguila, J. (2018). Automated early yield prediction in vineyards from on-the-go image acquisition. Computers and Electronics in Agriculture, 144, 26–36. https://doi.org/10.1016/j.compag.2017.11.026

4. Badrinarayanan, V., Kendall, A., & Cipolla, R. (2017). SegNet: A deep convolutional encoder-decoder architecture for image segmentation. IEEE Transactions on Pattern Analysis and Machine Intelligence, 39(12), 2481–2495. https://doi.org/10.1109/TPAMI.2016.2644615

5. Bargoti, S., & Underwood, J. (2017). Deep fruit detection in orchards. In 2017 IEEE International Conference on Robotics and Automation (ICRA) (pp. 3626–3633). IEEE.

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