Abstract: Seismic forward modeling plays a crucial role in Earth science, particularly in seismic exploration. It is essential for seismic data acquisition, inversion, and interpretation. Traditional ...
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 ...
Abstract: The increasing complexity of Analog/Mixed-Signal (AMS) schematics has been posing significant challenges in structure recognition, particularly in the intellectual property (IP) industry, ...
SVG Autoencoder - Uses a frozen representation encoder with a residual branch to compensate the information loss and a learned convolutional decoder to transfer the SVG latent space to pixel space.
Some results have been hidden because they may be inaccessible to you
Show inaccessible results
Feedback