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Mar, 2021
季节对比:来自未经筛选的遥感数据的无监督预训练
Seasonal Contrast: Unsupervised Pre-Training from Uncurated Remote Sensing Data
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Oscar Mañas, Alexandre Lacoste, Xavier Giro-i-Nieto, David Vazquez, Pau Rodriguez
TL;DR
提出了 Seasonal Contrast (SeCo) 管道来利用未标记数据进行领域内预训练遥感表示,并展示了使用该管道训练的模型在多个下游任务中实现了比 ImageNet 预训练模型和最先进的自监督学习方法更好的性能。
Abstract
remote sensing
and automatic earth monitoring are key to solve global-scale challenges such as disaster prevention, land use monitoring, or tackling climate change. Although there exist vast amounts of
remote sensing
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