Search Results for author: Muhammad Saif-ur-Rehman

Found 7 papers, 0 papers with code

Adaptive SpikeDeep-Classifier: Self-organizing and self-supervised machine learning algorithm for online spike sorting

no code implementations30 Mar 2023 Muhammad Saif-ur-Rehman, Omair Ali, Christian Klaes, Ioannis Iossifidis

The proposed algorithm is the first spike sorting algorithm that automatically learns the abrupt changes in the distribution of noise and SA.

Spike Sorting

ConTraNet: A single end-to-end hybrid network for EEG-based and EMG-based human machine interfaces

no code implementations21 Jun 2022 Omair Ali, Muhammad Saif-ur-Rehman, Tobias Glasmachers, Ioannis Iossifidis, Christian Klaes

Approach: In this work, we introduce a single hybrid model called ConTraNet, which is based on CNN and Transformer architectures that is equally useful for EEG-HMI and EMG-HMI paradigms.

EEG Electroencephalogram (EEG) +3

Deep Transfer-Learning for patient specific model re-calibration: Application to sEMG-Classification

no code implementations30 Dec 2021 Stephan Johann Lehmler, Muhammad Saif-ur-Rehman, Tobias Glasmachers, Ioannis Iossifidis

In this study, we investigate the effectiveness of transfer learning using weight initialization for recalibration of two different pretrained deep learning models on a new subjects data, and compare their performance to subject-specific models.

Domain Adaptation Transfer Learning

Anchored-STFT and GNAA: An extension of STFT in conjunction with an adversarial data augmentation technique for the decoding of neural signals

no code implementations30 Nov 2020 Omair Ali, Muhammad Saif-ur-Rehman, Susanne Dyck, Tobias Glasmachers, Ioannis Iossifidis, Christian Klaes

GNAA is not only an augmentation method but is also used to harness adversarial inputs in EEG data, which not only improves the classification accuracy but also enhances the robustness of the classifier.

Classification Data Augmentation +2

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