2021 · 19 citations · 12 references
ComputingComputer ScienceEarth SciencesComputer VisionMachine LearningRemote SensingDeep LearningImage ClassificationRemote Sensing Image AnalysisRemote Sensing ImageryScene UnderstandingSemantic SegmentationConvolutional Neural Network SegmentationConvolutional Neural NetworksDeep Learning-based ClassificationMachine Learning For Sea Ice ClassificationSar InterpretationScene Classification With Deep LearningSea Ice Mapping From Satellite DataSea Ice Type Classification
In this paper we focus on automated sea ice mapping based on satellite images with deep learning methods. We adjust the UNET++ convolutional neural network architecture for sea ice type semantic segmentation and create a per-pixel classifier for Sentinel-1 SAR scenes. The classification is done tile-wise, i.e. a Sentinel-1 scene is divided into tiles, classified, and then the results are joined back to form the classified scene. We address to the border effect appearing when a tiled classification is applied.
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