BriefGPT.xyz
Oct, 2023
跨注意力时空上下文变换器用于历史地图语义分割
Cross-attention Spatio-temporal Context Transformer for Semantic Segmentation of Historical Maps
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Sidi Wu, Yizi Chen, Konrad Schindler, Lorenz Hurni
TL;DR
提取历史地图的信息是一项具有挑战性的任务,尤其是在考虑到数据依赖性不确定性的情况下,我们提出了一种融合时空特征和交叉注意力变换器的U-Net网络(U-SpaTem),该模型在分割任务上表现出比其他方法更好的性能。
Abstract
historical maps
provide useful spatio-temporal information on the Earth's surface before modern earth observation techniques came into being. To extract information from maps,
neural networks
, which gain wide pop
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