Abstract: Recently, deep learning has attracted intensive attentions in electromagnetic society, especially for inverse problems. In this work, we propose two language-guided automatic design ...
Abstract: This paper proposes a collaborative variational autoencoder (VAE)-based target fusion method for sixth-generation (6G) intelligent cooperative integrated sensing and communication (IC-ISAC) ...
MAESTRO: Masked Autoencoders for Multimodal, Multitemporal, and Multispectral Earth Observation Data
MAESTRO_FLAIR-HUB_base — pre-trained on FLAIR-HUB MAESTRO_S2-NAIP-urban_base — pre-trained on S2-NAIP-urban Land cover segmentation in France, with 12 semantic classes. Note that the FLAIR#2 version ...
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