Categories: AI/ML News

Self-supervised AI learns physics to reconstruct microscopic images from holograms

Researchers have unveiled an artificial intelligence-based model for computational imaging and microscopy without training with experimental objects or real data. The team introduced a self-supervised AI model nicknamed GedankenNet that learns from physics laws and thought experiments. Informed only by the laws of physics that universally govern the propagation of electromagnetic waves in space, the researchers taught their AI model to reconstruct microscopic images using only random artificial holograms — synthesized solely from ‘imagination’ without relying on any real-world experiments, actual sample resemblances or real data.
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