Semantic segmentation sample augmentation based on simulated scene generation—case study on dock extraction from high spatial resolution imagery
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DOI: 10.1080/01431161.2021.1907866
Abstract: ABSTRACT Deep learning-based semantic segmentation methods, such as fully convolutional networks (FCNs), are state-of-the-art techniques for object extraction from high spatial resolution images. However, collecting massive scene-formed training samples typically required in FCNs is time-consuming… read more here.
Keywords: sample; extraction; sample augmentation; dock extraction ... See more keywords