Publications
- Transfer Learning based Motor Imagery Classification Using Convolutional Neural Networks
In 2019 27th Iranian Conference on Electrical Engineering (ICEE). IEEE
Available here. - Deep Learning for ECG Biometrics: A Survey
In Preparation, To be submitted to IEEE Access journal. - * My Google Scholar
Projects
- Motor Imagery EEG Classification | python, MATLAB
Deep learning methods: DNN, CNN, LSTM, GRU, RNN, Transformers.
Machine learning methods: ELM, SVM, Contrastive Learning.
Feature extraction: CSP, FBCSP, Wavelet, FFT. - EEG Data Augmentation | python, MATLAB
GAN, Autoencoders, Noise augmentation, Amplitude perturbation. - User Identification | python
Using EEG Signals.
Deep Learning methods: CNN, LSTM, CNN-LSTM. (Code available here) - Object Detection | python
Deep learning methods: Different version of YOLO networks.
Evaluate on our private vehicle detection and tracking dataset. - Anomaly Detection | python
Deep learning methods: Autoencoders, GANomaly, AnoGAN.
Evaluate on MVTec dataset and our own dataset. - Audio scene classification | python
Deep learning methods: CNN, GRU, CNN-GRU.
Evaluate on LITIS Rouen dataset. (Code available here) - ECG recognition | python
Python reproducible framework covering multiple stages of ECG-based biometric systems
Currently working on and continuously updating. (Code available here) - Iris recognition | python
Python reproducible framework covering multiple stages of iris-based biometric systems
Private python framework worked at IEBI lab at UniMi. - * My Github