Detection and recognition of tea buds by integrating deep learning and image-processing algorithm-Reference-Cited by-同舟云学术

Detection and recognition of tea buds by integrating deep learning and image-processing algorithm

Published:2024-02-10 Issue:4 Volume:18 Page:2744-2761
ISSN:2193-4126
Container-title:Journal of Food Measurement and Characterization
language:en
Short-container-title:Food Measure

Author:

Liu Fei,Wang Shudong^ORCID,Pang Shanchen,Han Zhongzhi

Funder

National Key Research and Development Program of China

National Natural Science Foundation of China

Publisher

Springer Science and Business Media LLC

Link

https://link.springer.com/content/pdf/10.1007/s11694-023-02351-3.pdf

Reference45 articles.

1. S.Y. Pan, Q. Nie, H.C. Tai, X.L. Song, Y.F. Tong, L.J.F. Zhang, X.W. Wu, Z.H. Lin, Y.Y. Yu, D.Y. Ye, Y. Zhang, X.Y. Wang, P.L. Zhu, Z.S. Chu, Z.L. Yu, C. Liang, Tea and tea drinking: China’s outstanding contributions to the mankind. Chin. Med. 17(1), 1–40 (2022)

2. FAO, International tea market: market situation, prospects and emerging issues (2022), https://www.fao.org/3/cc0238en/cc0238en.pdf. Accessed 6 Apr 2023

3. J.E. Lee, B.J. Lee, J.O. Chung, H.N. Kim, E.H. Kim, S. Jung, H. Lee, Y.S. Hong, Metabolomic unveiling of a diverse range of green tea (Camellia sinensis) metabolites dependent on geography. Food Chem. 174, 452–459 (2015)

4. C.W. Dong, H.K. Zhu, J.W. Zhao, Y.W. Jiang, H.B. Yuan, Q.S. Chen, Sensory quality evaluation for appearance of needle-shaped green tea based on computer vision and nonlinear tools. J. Zhejiang Univ. Sci. B 18(6), 544 (2017)

5. Y.T. Li, S.K. Wu, L.Y. He, J.H. Tong, R.M. Zhao, J.M. Jia, J.N. Chen, C.Y. Wu, Development and field evaluation of a robotic harvesting system for plucking high-quality tea. Comput. Electron. Agric. 206, 107659 (2023)

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1. A lightweight tea buds detection model with occlusion handling;Journal of Food Measurement and Characterization;2024-07-10