M
Mehedi Masud
Researcher at Taif University
Publications - 171
Citations - 2877
Mehedi Masud is an academic researcher from Taif University. The author has contributed to research in topics: Computer science & Data sharing. The author has an hindex of 16, co-authored 171 publications receiving 978 citations. Previous affiliations of Mehedi Masud include Ottawa University & Universiti Teknologi MARA.
Papers
More filters
Journal ArticleDOI
Medical image-based detection of COVID-19 using Deep Convolution Neural Networks.
TL;DR: This study presents a practical solution to detect COVID-19 from chest X-rays while distinguishing those from normal and impacted by Viral Pneumonia via Deep Convolution Neural Networks (CNN).
Journal ArticleDOI
A Lightweight and Robust Secure Key Establishment Protocol for Internet of Medical Things in COVID-19 Patients Care
Mehedi Masud,Gurjot Singh Gaba,Salman A. AlQahtani,Ghulam Muhammad,Brij B. Gupta,Pardeep Kumar,Ahmed Ghoneim +6 more
TL;DR: This article proposes a lightweight and physically secure mutual authentication and secret key establishment protocol that uses physical unclonable functions (PUFs) to enable the network devices to verify the doctor’s legitimacy and sensor node before establishing a session key.
Journal ArticleDOI
Nature-Inspired-Based Approach for Automated Cyberbullying Classification on Multimedia Social Networking
N. Yuvaraj,K. Srihari,Gaurav Dhiman,K. Somasundaram,Ashutosh Sharma,S. Rajeskannan,Mukesh Soni,Gurjot Singh Gaba,Mohammed A. AlZain,Mehedi Masud +9 more
TL;DR: An integrated model is proposed that combines both the feature extraction engine and classification engine from the input raw text datasets from a social media engine and shows that the ANN-DRL has higher classification results than conventional machine learning classifiers.
Journal ArticleDOI
Design of Multi-Information Fusion Based Intelligent Electrical Fire Detection System for Green Buildings
Ren Xiaogeng,Li Chunwang,Ma Xiaojun,Chen Fuxiang,Haoyu Wang,Ashutosh Sharma,Gurjot Singh Gaba,Mehedi Masud +7 more
TL;DR: This paper introduces in detail a fault identification method based on multi-information fusion, which can consolidate the complementary advantages of different types of judgment in fault identification and prevents electrical fires in green buildings more comprehensively and accurately.
Journal ArticleDOI
An enhanced k -means clustering algorithm for pattern discovery in healthcare data
TL;DR: This work studies k-means clustering algorithms on large datasets and presents an enhancement to k-Means clustered, which requires k or a lesser number of passes to a dataset, and shows that G-mean outperforms k-MEans in terms of entropy and F-scores.