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We analyze the regression accuracy of convolutional neural networks assembled from encoders, decoders and skip connections and trained with multifidelity data. Besides requiring significantly less trainable parameters than equivalent fully connected
Externí odkaz:
http://arxiv.org/abs/2205.05187
Novel Magnetic Resonance (MR) imaging modalities can quantify hemodynamics but require long acquisition times, precluding its widespread use for early diagnosis of cardiovascular disease. To reduce the acquisition times, reconstruction methods from u
Externí odkaz:
http://arxiv.org/abs/2201.03715
Publikováno v:
In Biomedical Signal Processing and Control July 2023 84
Autor:
Partin, Lauren, Geraci, Gianluca, Rushdi, Ahmad A., Eldred, Michael S., Schiavazzi, Daniele E.
Publikováno v:
In Journal of Computational Physics 1 January 2023 472