Classification of weed using machine learning techniques: a review—challenges, current and future potential techniques
Author:
Publisher
Springer Science and Business Media LLC
Subject
Horticulture,Plant Science,Agronomy and Crop Science
Link
https://link.springer.com/content/pdf/10.1007/s41348-022-00612-9.pdf
Reference120 articles.
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2. Adams J, Qiu Y, Xu Y, Schnable JC (2020) Plant segmentation by supervised machine learning methods. Plant Phenom J 3(1):e20001. https://doi.org/10.1002/ppj2.20001
3. Adhikari SP, Yang H, Kim H (2019) Learning semantic graphics using convolutional encoder–decoder network for autonomous weeding in paddy. Front Plant Sci 10:1404. https://doi.org/10.3389/fpls.2019.01404
4. Ahmed F, Al-Mamun HA, Bari AH, Hossain E, Kwan P (2012) Classification of crops and weeds from digital images: a support vector machine approach. Crop Prot 40:98–104. https://doi.org/10.1016/j.cropro.2012.04.024
5. Alam M, Alam MS, Roman M, Tufail M, Khan MU, Khan MT (2020) Real-time machine-learning based crop/weed detection and classification for variable-rate spraying in precision agriculture. In: 2020 7th international conference on electrical and electronics engineering (ICEEE). IEEE, pp 273–280. https://doi.org/10.1109/ICEEE49618.2020.9102505
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