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- W4285200145 abstract "Farmers across the world are looking for more efficient ways to collect data about various plant physiological factors. This data collection is conventionally done using manual methods, which are time-consuming and labor intensive. Remote sensing technologies (aerial and ground based) combined with machine learning techniques can be used for high-throughput phenotyping and provide critical information for precision crop management. In this chapter, different types of unmanned aerial vehicles (UAVs) equipped with various types of sensors are presented. The advantages and disadvantages of each type of UAV and sensing system are discussed for precision agriculture applications. Furthermore, an overview of artificial intelligence algorithms is presented with examples of their usage in precision agriculture. Machine learning, which is an application of AI, is used to process and analyze data generated by these remote sensing systems. These algorithms are used for their capabilities to process complex big data to estimate plant needs and predict production." @default.
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- W4285200145 date "2022-01-01" @default.
- W4285200145 modified "2023-09-25" @default.
- W4285200145 title "Applications of UAVs and Machine Learning in Agriculture" @default.
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- W4285200145 doi "https://doi.org/10.1007/978-981-19-2027-1_1" @default.
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