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Palabras clave – provistas por la editorial

convolutional neural network; image segmentation; multi-scale feature fusion; semantic features; Gaofen 6; aerial images; land-use; Tai’an; convolutional neural networks (CNNs); feature fusion; ship detection; optical remote sensing images; end-to-end detection; transfer learning; remote sensing; single shot multi-box detector (SSD); You Look Only Once-v3 (YOLO-v3); Faster RCNN; statistical features; Gaofen-2 imagery; winter wheat; post-processing; spatial distribution; Feicheng; China; light detection and ranging; LiDAR; deep learning; convolutional neural networks; CNNs; mask regional-convolutional neural networks; mask R-CNN; digital terrain analysis; resource extraction; hyperspectral image classification; few-shot learning; quadruplet loss; dense network; dilated convolutional network; artificial neural networks; classification; superstructure optimization; mixed-inter nonlinear programming; hyperspectral images; super-resolution; SRGAN; model generalization; image downscaling; mixed forest; multi-label segmentation; semantic segmentation; unmanned aerial vehicles; classification ensemble; machine learning; Sentinel-2; geographic information system (GIS); earth observation; on-board; microsat; mission; nanosat; AI on the edge; CNN