Abstract In recent years. the integration of deep learning techniques with biophotonic setups has opened new horizons in bioimaging. A compelling trend in this field involves deliberately compromising certain measurement metrics to engineer better bioimaging tools in terms of e. g. https://globechemicalcompanyls.shop/product-category/roll-towel/
Neural network-based processing and reconstruction of compromised biophotonic image data
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