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- W4366147043 abstract "In this paper, we explore the capabilities of UAV sensing, and its photogrammetry product-orthomosaic by using convolutional neural network for semantic segmentation of litchi tree crown. We prepare an UAV-Litchi dataset consisting of 12 large orthomosaics having a total of 3000 image patches of size $256 times 256$. The litchi tree crown is segmented by using the U-Net and smooth bending method. Finally, testing is performed over large aerial images of $3500 times 3500$ size to provide a complete segmentation map of the crop region. The proposed model show mIoU score of 89 % and F1 score of 98 % with UAV-Litchi dataset, while mIoU score of 78 % and F1 score of 91 % with the benchmark Potsdam dataset." @default.
- W4366147043 created "2023-04-19" @default.
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- W4366147043 date "2023-01-23" @default.
- W4366147043 modified "2023-09-26" @default.
- W4366147043 title "UAV sensing-based semantic image segmentation of litchi tree crown using deep learning" @default.
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- W4366147043 doi "https://doi.org/10.1109/apscon56343.2023.10101133" @default.
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