A physics-informed fine-tuning step adapts a pre-trained deep network to reconstruct sound sources on a new, limited-data target using a single pressure measurement.
A cylindrical near-field acoustical holography method based on cylindrical translation window expansion and an autoencoder stacked with 3d-cnn layers,
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Physics-Informed Transfer Learning for Data-Driven Sound Source Reconstruction in Near-Field Acoustic Holography
A physics-informed fine-tuning step adapts a pre-trained deep network to reconstruct sound sources on a new, limited-data target using a single pressure measurement.