Prithvi-EO-2.0 is based on the ViT architecture, pretrained using a masked autoencoder (MAE) approach, with two major modifications as shown in the figure below. Second, we considered geolocation ...
Abstract: In an era of massive IoT, ultra-low-voltage and ultra-low-power wireless transceivers powered directly by energy harvesters, e.g. solar cells at 0.5V, are highly demanded to remove battery ...
Abstract: The in-context learning capability of Large Language Models has achieved significant success in text-to-SQL task. Most existed approaches generally adopt a straightforward three-stage ...
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