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- W4387607576 abstract "The field of remote sensing, encompassing applications ranging from environmental monitoring and disaster management to agriculture and urban planning, is experiencing a transformational revolution, driven by the power of deep learning. This article delves into the innovative and successful deep learning architectures, with a primary focus on Convolutional Neural Networks (CNNs), that have emerged as game-changers in remote sensing, pushing the boundaries of what is possible and offering fresh perspectives on how we perceive and interact with our environment." @default.
- W4387607576 created "2023-10-14" @default.
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- W4387607576 date "2023-10-12" @default.
- W4387607576 modified "2023-10-14" @default.
- W4387607576 title "Optimizing Networks with Deep Learning: Exploring Successful Architectures in Remote Sensing, Including CNNs" @default.
- W4387607576 doi "https://doi.org/10.31219/osf.io/va4df" @default.
- W4387607576 hasPublicationYear "2023" @default.
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