A convolutional autoencoder trained only on simulated data can denoise angular streaking images and reconstruct up to three missing time-of-flight detectors, with fast inference for online experiments.
This normalization process can also be implemented in real-world scenarios where TOF detector failures occur
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Reconstructing Time-of-Flight Detector Values of Angular Streaking Using Machine Learning
A convolutional autoencoder trained only on simulated data can denoise angular streaking images and reconstruct up to three missing time-of-flight detectors, with fast inference for online experiments.