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Algorithms for semantic segmentation of multispectral remote sensing imagery using deep learning
2018
ISPRS journal of photogrammetry and remote sensing (Print)
Deep convolutional neural networks (DCNNs) have been used to achieve state-of-the-art performance on many computer vision tasks (e.g., object recognition, object detection, semantic segmentation) thanks to a large repository of annotated image data. Large labeled datasets for other sensor modalities, e.g., multispectral imagery (MSI), are not available due to the large cost and manpower required. In this paper, we adapt state-of-the-art DCNN frameworks in computer vision for semantic
doi:10.1016/j.isprsjprs.2018.04.014
fatcat:njpadtv6b5hqlpl72nyhlycrem