Using Computer Vision and Machine Learning Based Methods for Plant Monitoring in Agriculture: A Systematic Literature Review

Author:

Kempelis Arturs1,Romanovs Andrejs2,Patlins Antons3

Affiliation:

1. Riga Technical University,Faculty of Computer Science and Information Technology,Riga,Latvia

2. Riga Technical University,Department of Modelling and Simulation,Riga,Latvia

3. Riga Technical University,Faculty of Electrical and Environmental Engineering,Riga,Latvia

Publisher

IEEE

Cited by 8 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. Review on Application of Vision Transformers in IoT Edge Devices for Plant Sensor Measurement Forecasting;2024 IEEE 11th Workshop on Advances in Information, Electronic and Electrical Engineering (AIEEE);2024-05-31

2. Smart Plant Monitoring: An Integrated IoT System for Sustainable Precision Agriculture;2024 MIT Art, Design and Technology School of Computing International Conference (MITADTSoCiCon);2024-04-25

3. Computer Vision and Machine Learning-Based Predictive Analysis for Urban Agricultural Systems;Future Internet;2024-01-28

4. Advancements in Imaging Sensors and AI for Plant Stress Detection: A Systematic Literature Review;Plant Phenomics;2024-01

5. Significant roles of smart sensors in the modern agriculture and food industry;Food Industry 4.0;2024

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