In this blog, we propose a neural network architecture that is able to differentiate whether people are wearing face masks in a real-time setting. This can be potentially used to monitor individuals who are not wearing face masks in a crowd, which can be useful for many different applications, like research on contagiousness of the virus and for supervision purposes. An approach is shown how to practically train and test a neural network model with a non-standard self-augmented dataset in the topic of image recognition in computer vision. …

DECODE seems a promising computational tool to localize single emitters at high density in 3D from 2D image frames. For personal educational purposes, we have tried to reproduce DECODE as it was represented in the paper by Artur Speiser et al. called “Deep learning enables fast and dense single-molecule localization with high accuracy”. This was done using namely the PyTorch library of Python. DECODE distinguishes itself by reduced imaging time and improved accuracy in comparison to competing networks e.g. DeepSTORM3D and CSpline. …

Mahir Sabanoglu

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