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Found 4 papers, 1 papers with code
AutoPhaseNN: Unsupervised Physics-aware Deep Learning of 3D Nanoscale Bragg Coherent Diffraction Imaging
The problem of phase retrieval, or the algorithmic recovery of lost phase information from measured intensity alone, underlies various imaging methods from astronomy to nanoscale imaging.
Real-time 3D Nanoscale Coherent Imaging via Physics-aware Deep Learning
Phase retrieval, the problem of recovering lost phase information from measured intensity alone, is an inverse problem that is widely faced in various imaging modalities ranging from astronomy to nanoscale imaging.
Cost-sensitive detection with variational autoencoders for environmental acoustic sensing
Environmental acoustic sensing involves the retrieval and processing of audio signals to better understand our surroundings.
Mosquito detection with low-cost smartphones: data acquisition for malaria research
Mosquitoes are a major vector for malaria, causing hundreds of thousands of deaths in the developing world each year.
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