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Novel deep learning and remote sensing approaches in environmental applications
José Marcato Junior (1)
(1) Federal University of Mato Grosso do Sul, Campo Grande, Brasil
In my lecture, I will discuss various aspects of how artificial intelligence can significantly enhance accurate mapping through remote sensing data from different platforms, including UAV, and orbital sources. I will introduce a range of strategies aimed at optimizing outcomes and enabling the development of generalized deep-learning models. Additionally, I will explore techniques for reducing the reliance on labeled data and will showcase practical results in the context of environmental applications and precision agriculture.
Ключевые слова: deep learning, remote sensing
Ссылка для цитирования: José Marcato.Junior. Novel deep learning and remote sensing approaches in environmental applications // Материалы 21-й Международной конференции «Современные проблемы дистанционного зондирования Земли из космоса». Москва: ИКИ РАН, 2023. C. 459. DOI 10.21046/21DZZconf-2023aXIX Международная научная Школа-конференция молодых ученых по фундаментальным проблемам дистанционного зондирования Земли из космоса
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