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Interested in #microscopy and #DeepLearning? We introduce DeepTrack 2.0, a framework to design, train, and validate deep-learning solutions for digital microscopy. Check our article in Applied Physics Reviews! aip.scitation.org/doi/10.1063/5.…

Applying real-time data augmentation for training neural networks has never been easier! With DeepTrack 2.0, this is possible in a few steps. Try it yourself! Learn more: github.com/softmatterlab/…

Always wanted to use deep learning for microscopy, but never dared? DeepTrack 2.0 for quantitative microscopy with deep learning is now published Applied Physics Reviews Great work by Benjamin Midtvedt Saga Helgadottir Aykut Argun Jesús Daniel Midtvedt aip.scitation.org/doi/10.1063/5.…

AI banar vägen! Bilder tagna med mikroskop är fullproppade med information som är svår att komma åt. Nu finns ett nytt AI-verktyg som underlättar processen, och banar väg för en mängd nya användningsområden inom både forskning och industri. bit.ly/3ktQrs8

DeepTrack allows you to generate synthetic data by imaging cell-like objects through a simulated fluorescence microscope! The simulated data can be further use to train a neural network for cell counting, tracking, or segmentation. Learn more: youtube.com/watch?v=hyfaxF…

DeepTrack 2.0 is on the news (now in english)! gu.se/en/news/new-ai…

Our paper on #DeepLearning to extract relevant quantitative biological information from brightfield cell images is published on Biophysics Reviews! aip.scitation.org/doi/pdf/10.106…

Feeling the peer pressure #myfirstTweet

Henrik Lundquist bare: #IIHFWorlds #sweden #sverige #kinghenrik #nyrangers #nhl