用无人机检测植物病害病原体

Jakub Karbowski, Jedrzej Minda
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引用次数: 0

摘要

如今,无人机已经广泛应用于农业和林业。无人机可以帮助喷洒植物,进行地面测量,并估计恶劣天气条件或野生动物造成的损害。无人机还可以用于照顾农作物的状况。传统的检测植物病害威胁的方法既耗时又无效。由于使用配备了适当视觉系统的无人机,可以对植物的状况进行快速和精确的控制。本文提出了一种利用无人机检测植物病原体的系统。介绍了提出的解决方案的概念和工厂监测的方法。介绍了多种神经网络结构的应用。由于使用了各种数据集,描述了可信的模型性能指标。此外,本文还介绍了所开发算法在试验场的测试结果。所进行的研究证实了在监测森林作物和生态系统中使用无人机的合法性和有效性。
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USING A DRONE TO DETECT PLANT DISEASE PATHOGENS
Today, drones are already widely used in agriculture and forestry. Drones can help spray plants, take surface measurements, and estimate the damage caused by adverse weather conditions or wild animals. Drones can also be used in caring for the condition of crops. Traditional methods of detecting threats related to plant disease are time-consuming and ineffective. Thanks to the use of drones equipped with appropriate vision systems, it is possible to carry out quick and precise control of the condition of the plants. The article proposes a system for detecting plant pathogens using a drone. The concept of the proposed solution and the methodology of plant monitoring is described. The use of multiple neural network architectures is presented. Credible model performance metrics are described, thanks to the use of various datasets. In addition, the article presents the results of the developed algorithm on the testing ground. The conducted research confirmed the legitimacy and validity of the use of drones in the monitoring of forest crops and ecosystems.
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