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## Graphical user interface
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DeepTrack 2.0 provides a completely stand-alone [graphical user interface](https://github.com/BenjaminMidtvedt/DeepTrack-app.git), which delivers all the power of DeepTrack without requiring programming knowledge.
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DeepTrack 2.0 provides a completely stand-alone [graphical user interface](https://github.com/softmatterlab/DeepTrack-2.0-app), which delivers all the power of DeepTrack without requiring programming knowledge.
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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." [arXiv:2010.08260](https://arxiv.org/abs/2010.08260)
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Benjamin Midtvedt, Saga Helgadottir, Aykut Argun, Jesús Pineda, Daniel Midtvedt, Giovanni Volpe. "Quantitative Digital Microscopy with Deep Learning." [arXiv:2010.08260](https://arxiv.org/abs/2010.08260)
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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. "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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Saga Helgadottir, Aykut Argun, and Giovanni Volpe. "DeepTrack." https://github.com/softmatterlab/DeepTrack.git (2019).
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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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