Ghulam Muhammad

TL;DR: It is demonstrated that the novel MCNN and CCNN fusion methods outperforms all the state-of-the-art machine learning and deep learning techniques for EEG classification.

TL;DR: Experimental results confirm the effectiveness of the proposed system involving the CNNs and the ELMs, which is evaluated using two audio–visual emotional databases, one of which is Big Data.

TL;DR: A B5G framework is proposed that utilizes the 5G network's low-latency, high-bandwidth functionality to detect COVID-19 using chest X-ray or CT scan images, and to develop a mass surveillance system to monitor social distancing, mask wearing, and body temperature.

TL;DR: This work systematically review the DL-based research for MI-EEG classification from the past ten years, summarizes MI- EEG-based applications, extensively explores public MI-eeG datasets, and gives an overall visualization of the performance attained for each dataset based on the reviewed articles.