Ashok Parmar's Projects
Automatic modulation classification using deep learning
Config files for my GitHub profile.
A curated list of awesome open source libraries to deploy, monitor, version and scale your machine learning
Useful RadioML Examples
A CNN-RNN architecture created for auto captioning of an image
a CNN Model is implemented to classify the MNIST dataset
A CNN model implemented for classification of MNIST fashion dataset
NeuroKit2: The Python Toolbox for Neurophysiological Signal Processing
Datasets for AMC in NOMA system
A PDDL Solver in C++.
Radio modulation recognition with CNN, CLDNN, CGDNN and MCTransformer architectures. Best results were achieved with the CGDNN architecture, which has roughly 50,000 parameters, and the final model has a memory footprint of 636kB. More details can be found in my bachelor thesis linked in the readme file.
Stress classifier with AutoML