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Using multi-task learning to capture signals simultaneously from the fovea efficiently and the neighboring targets in the peripheral vision generate a visual response map. A calibration-free user-independent solution, desirable for clinical diagnostics. A stepping stone for an objective assessment of glaucoma patients’ visual field.

Home Page: https://jinglescode.github.io/ssvep-multi-task-learning/

License: BSD 2-Clause "Simplified" License

Python 100.00%
eeg deep-learning convolutional-neural-network pytorch brain-computer-interface bci cnn multitask-learning ssvep

ssvep-multi-task-learning's Introduction

Hong Jing (Jingles)

Software Development • Machine Learning • Blockchain

GitHub GitHub LinkedIn LinkedIn LinkedIn Stack Overflow


Currently working on...

  • PhD research, applying machine learning to neuroscience and healthcare. Specifically, I work on brain-computer interfaces to diagnose eye problems. It is a fascinating combination between AI and Neuroscience.

  • w3, a free URL shortener service that is fast and fuss-free.

  • Satcom, a web extension that add collaborative layer to your Internet browsing experience.

  • Mesh SDK, an open-source software development kit library to easily build decentralized applications.

  • Write about machine learning, machine learning and self-improvement on my blog and Medium.

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ssvep-multi-task-learning's Issues

About the data part of the code

hello!
Your code only contains the model part, not the part of how the data runs in the model, could you please add this part as well? I can't use your repository without the data part,thanks!

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