Single-plant broccoli growth monitoring using deep learning with UAV imagery-Reference-Cited by-同舟云学术

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Single-plant broccoli growth monitoring using deep learning with UAV imagery

Published:2023-04 Issue: Volume:207 Page:107739
ISSN:0168-1699
Container-title:Computers and Electronics in Agriculture
language:en
Short-container-title:Computers and Electronics in Agriculture

Author:

Lee Cheng-Ju,Yang Ming-Der,Tseng Hsin-Hung,Hsu Yu-Chun,Sung Yu,Chen Wei-Ling

Funder

National Science and Technology Council

Ministry of Science and Technology

Publisher

Elsevier BV

Subject

Horticulture,Computer Science Applications,Agronomy and Crop Science,Forestry

Reference48 articles.

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2. Agüera, F., Carvajal, F., Pérez, M., 2012. Measuring Sunflower Nitrogen Status From an Unmanned Aerial Vehicle-Based System and an on the Ground Device. In: Proceedings of the ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, XXXVIII-1/(C22), pp. 33–37. 10.5194/isprsarchives-xxxviii-1-c22-33-2011.

3. Bah, M.D., Hafiane, A., Canals, R., 2017. Weeds detection in UAV imagery using SLIC and the hough transform. In: Proceedings of the 7th International Conference on Image Processing Theory, Tools and Applications, pp. 1–6. 10.1109/IPTA.2017.8310102.

4. Vineyard yield estimation by combining remote sensing, computer vision and artificial neural network techniques;Ballesteros;Precis. Agric.,2020

5. Evaluating multi-spectral images and vegetation indices for precision farming applications from UAV images;Candiago;Remote Sens. (Basel),2015

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