Dataset Groups Activity Stream RaSeedGAN: Randomly-SEEDed super-resolution GAN for sparse measurements A novel deep-learning approach based on generative adversarial networks to perform super-resolution reconstruction of sparse measurements. BibTex: @dataset{Alejandro_G¨uemes_and_Carlos_Sanmiguel_Vila_and_Stefano_Discetti_2024, abstract = {A novel deep-learning approach based on generative adversarial networks to perform super-resolution reconstruction of sparse measurements.}, author = {Alejandro G¨uemes and Carlos Sanmiguel Vila and Stefano Discetti}, doi = {10.57702/w5srv915}, institution = {No Organization}, keyword = {'GANs', 'Physics-informed neural networks', 'Sparse data', 'Super-resolution'}, month = {dec}, publisher = {TIB}, title = {RaSeedGAN: Randomly-SEEDed super-resolution GAN for sparse measurements}, url = {https://service.tib.eu/ldmservice/dataset/raseedgan--randomly-seeded-super-resolution-gan-for-sparse-measurements}, year = {2024} }
