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manli / backboned-unet
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The python code used for the numerical examples in the paper "Reconstructing anisotropic conductivities on two-dimensional Riemannian manifolds from power densities". A preprint of this paper is available on arXiv: https://arxiv.org/abs/2202.12056.
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The python code used for the numerical examples in the paper "Conductivity reconstruction from power density data in limited view". A preprint of this paper is available on arXiv: https://arxiv.org/abs/2202.12370.
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The python code used for the numerical examples in the paper "Jacobian of solutions to the conductivity equation in limited view". A preprint of this paper is available on arXiv: http://arxiv.org/abs/2207.03849.
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This is a zip comppres .ova file. It is an image of pre-configured Kali Linux machine used in realtion to the Cyber security roadshow - Hands on hacking developed by Andreas Breum and Christian Skou Pedersen.
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glia / Resting-state EEG analysis
Apache License 2.0This collection contains the code used to analyze the data that supports the findings from the following publication:
Qianliang Li, Maya Coulson Theodorsen, Ivana Konvalinka, Kasper Eskelund, Karen-Inge Karstoft, Søren Bo Andersen and Tobias S Andersen. Resting-state EEG functional connectivity predicts post-traumatic stress disorder subtypes in veterans. Journal of Neural Engineering, 2022 (https://doi.org/10.1088/1741-2552/ac9aaf).
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Code that demonstrates the proposed TMB and Kalman filter as shown in LINK
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manli / TopologyLayer
MIT LicenseA Topology Layer for Machine Learning : Persistent Homology + Features for PyTorch
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MTRNet++: One-stage Mask-based Scene Text Eraser
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manli / SceneTextRemover-pytorch
MIT LicenseThis is a minimal implementation of Scene text removal via cascaded text stroke detection and erasing. This github repository is for studying on image in-painting for scene text erasing. Thank you :)
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This project contains a small program with user interface implementing the drift correction method for image stack containing near spherical objects as described in Stephensen et. al. Communications biology 3.1 (2020)
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This project contains code for the AAAI Workshop paper "Probability trees and the value of a single intervention"
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