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To image, or not to image: class-specific diffractive cameras with all-optical erasure of undesired objects | eLight

Privacy protection is a growing concern in the digital era, with machine vision techniques widely used throughout public and private settings. Existing methods address this growing problem by, e.g., encrypting camera images or obscuring/blurring the imaged information through digital algorithms. Here, we demonstrate a camera design that performs class-specific imaging of target objects with instantaneous all-optical erasure of other classes of objects. This diffractive camera consists of transmissive surfaces structured using deep learning to perform selective imaging of target classes of objects positioned at its input field-of-view. After their fabrication, the thin diffractive layers collectively perform optical mode filtering to accurately form images of the objects that belong to a target data class or group of classes, while instantaneously erasing objects of the other data classes at the output field-of-view. Using the same framework, we also demonstrate the design of class-spec ....

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VPS: Rising Fuel Quality Issues Linked to Rising Fuel Costs

Steve Bee of testing firm VPS sets out the correlation between rising fuel costs and an increase in quality problems. ....

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Shortage of ICU Beds Did Not Drive COVID-19 Deaths

A nationwide data review showed no impact between ICU bed scarcity and COVID-19 deaths. ....

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Casting a wider net in zebrafish imaging

In this interview, News-Medical talks to Dr. Alex Lubin and Dr. Jason Otterstrom, about the use of deep learning powered automated microscopy and image analysis for in vivo Zebrafish screening. ....

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ANGPTL8/betatrophin improves glucose tolerance

The effect of ANGPTL8/betatrophin on glucose tolerance in Kunming mice of different ages and metabolic profiles in insulin-resistant HepG2 cells. ....

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