Metadata-Version: 2.1
Name: BiModNeuroCNN
Version: 0.1.0
Summary: Tools for bimodal training of CNNs, i.e. concurrent training with two data types
Home-page: https://github.com/cfcooney
Author: Ciaran Cooney
License: MIT License
Description: **BiModNeuroCNN**
        
        This is a package for training bimodal deep learning archtectures on dual streams 
        of neurological data. Package tested on Electroencephalography (EEG) and 
        function near-infrared stpectroscopy (fNIRS).
        
        Work in progress - more to be added in future.
        
        # Installation
        
        1. Install PyTorch: http://pytorch.org/
        2. Install Braindecode: https://github.com/braindecode/braindecode
        
        3. Install latest release of BiModNeuroCNN using pip:
        ```
        pip install bimodneurocnn
        ```
        
        ## Dataset
        Link to dataset to be added upon upcoming publication.
        
        ## Citing
        Paper currently under review.
        
        Braindecode was used to implement this package:
        >@article {HBM:HBM23730,
        >author = {Schirrmeister, Robin Tibor and Springenberg, Jost Tobias and Fiederer,
        >  Lukas Dominique Josef and Glasstetter, Martin and Eggensperger, Katharina and Tangermann, Michael and
        >  Hutter, Frank and Burgard, Wolfram and Ball, Tonio},
        >title = {Deep learning with convolutional neural networks for EEG decoding and visualization},
        >journal = {Human Brain Mapping},
        >issn = {1097-0193},
        >url = {http://dx.doi.org/10.1002/hbm.23730},
        >doi = {10.1002/hbm.23730},
        >month = {aug},
        >year = {2017},
        >keywords = {electroencephalography, EEG analysis, machine learning, end-to-end learning, brainâ€“machine interface,
        >  brainâ€“computer interface, model interpretability, brain mapping},
        >}
        
        
        
        
Platform: UNKNOWN
Classifier: Intended Audience :: Developers
Classifier: Intended Audience :: Science/Research
Classifier: Topic :: Software Development :: Build Tools
Classifier: Topic :: Scientific/Engineering :: Artificial Intelligence
Classifier: Programming Language :: Python :: 3.6
Description-Content-Type: text/markdown
