Scientific Paper
Multi-Frame Super Resolution with Dual Pyramid Multi-Attention Network for Droplet Measurement
Summary
A deep-learning network for multi-frame super resolution sharpens low-quality images of micrometre droplets in flight during inkjet printing. Pyramid-based alignment, gated attention fusion and a self-attention reconstruction stage give state-of-the-art results on three benchmarks and cut the droplet measurement error from 3.34% to 2.52%.
Summary written by the openQCM team. The original abstract is on the publisher’s page.
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