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Update master readme
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README.md

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DeepTrack is a comprehensive deep learning framework for digital microscopy.
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We provide tools to create physical simulations of customizable optical systems, to generate and train neural network models, and to analyze experimental data.
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If you use DeepTrack 2.0 in your project, please cite our DeepTrack 2.0 article:
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```
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Benjamin Midtvedt, Saga Helgadottir, Aykut Argun, Jesús Pineda, Daniel Midtvedt, Giovanni Volpe.
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"Quantitative Digital Microscopy with Deep Learning."
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Applied Physics Reviews 8 (2021), 011310.
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https://doi.org/10.1063/5.0034891
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```
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# Getting started
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## Installation
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## Cite us!
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If you use DeepTrack 2.0 in your project, please cite us here:
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Benjamin Midtvedt, Saga Helgadottir, Aykut Argun, Jesús Pineda, Daniel Midtvedt, Giovanni Volpe. "Quantitative Digital Microscopy with Deep Learning." [https://doi.org/10.1063/5.0034891](https://aip.scitation.org/doi/10.1063/5.0034891)
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```
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Benjamin Midtvedt, Saga Helgadottir, Aykut Argun, Jesús Pineda, Daniel Midtvedt, Giovanni Volpe.
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"Quantitative Digital Microscopy with Deep Learning."
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Applied Physics Reviews 8 (2021), 011310.
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https://doi.org/10.1063/5.0034891
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```
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See also:
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Saga Helgadottir, Aykut Argun, and Giovanni Volpe. "Digital video microscopy enhanced by deep learning." Optica 6.4 (2019): 506-513. [10.1364/OPTICA.6.000506](https://doi.org/10.1364/OPTICA.6.000506)
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Saga Helgadottir, Aykut Argun, and Giovanni Volpe. "DeepTrack." https://github.com/softmatterlab/DeepTrack.git (2019).
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```
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Saga Helgadottir, Aykut Argun, and Giovanni Volpe.
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"Digital video microscopy enhanced by deep learning."
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Optica 6.4 (2019): 506-513.
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https://doi.org/10.1364/OPTICA.6.000506
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```
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```
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Saga Helgadottir, Aykut Argun, and Giovanni Volpe.
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"DeepTrack." (2019)
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https://github.com/softmatterlab/DeepTrack.git
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```
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## Funding
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This work was supported by the ERC Starting Grant ComplexSwimmers (Grant No. 677511).

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