Mohamed Hammad
Mohamed Hammad
Assistant Professor at faculty of computers and information, Menoufia University
Verified email at ci.menofia.edu.eg - Homepage
Title
Cited by
Cited by
Year
Multimodal biometric authentication systems using convolution neural network based on different level fusion of ECG and fingerprint
M Hammad, Y Liu, K Wang
IEEE Access 7, 26527-26542, 2018
332018
Detection of abnormal heart conditions based on characteristics of ECG signals
M Hammad, A Maher, K Wang, F Jiang, M Amrani
Measurement 125, 634-644, 2018
322018
Parallel score fusion of ECG and fingerprint for human authentication based on convolution neural network
M Hammad, K Wang
Computers & Security 81, 107-122, 2019
182019
Cancelable biometric authentication system based on ECG
M Hammad, G Luo, K Wang
Multimedia Tools and Applications 78 (2), 1857-1887, 2019
162019
Very deep feature extraction and fusion for arrhythmias detection
M Amrani, M Hammad, F Jiang, K Wang, A Amrani
Neural Computing and Applications 30 (7), 2047-2057, 2018
162018
A novel two-dimensional ECG feature extraction and classification algorithm based on convolution neural network for human authentication
M Hammad, S Zhang, K Wang
Future Generation Computer Systems 101, 180-196, 2019
132019
Progress in Outlier Detection Techniques: A Survey
H Wang, MJ Bah, M Hammad
IEEE Access 7, 107964 - 108000, 2019
82019
Fingerprint Classification Based on a Q-Gaussian Multi-class Support Vector Machine
H Mohamed, W Kuanquan
2017 International Conference on Biometrics Engineering and Application, 39-44, 2017
82017
Ear verification based on a novel local feature extraction
O Ibrahim, E Mahmoud, H Mohamed, Z Wangmeng
2017 International Conference on Biometrics Engineering and Application, 28-32, 2017
6*2017
A Novel Biometric Based on ECG Signals and Images for Human Authentication
H Mohamed, I Mina, H Mohiy
Int. Arab J. Inf. Technol, 959-964, 2016
62016
ResNet‐Attention model for human authentication using ECG signals
M Hammad, P Pławiak, K Wang, UR Acharya
Expert Systems, e12547, 2020
42020
A Novel Deep Transfer Learning Method for Detection of Myocardial Infarction
M Hammad
arXiv preprint arXiv:1906.09358, 2019
3*2019
Detection of abnormal heart conditions from the analysis of ECG signals
M Hammad, A Maher, K Adil, F Jiang, K Wang
11th International Conference on Bio-Inspired Systems and Signal Processing …, 2018
22018
Noisy COVID-19 X-ray Dataset
A sedik, N A. El-Hag, G M. El-Banby, A A. M. Khalaf, B Abd El-Rahiem, ...
https://data.mendeley.com/datasets/fjg5cbzffh/3, 2020
2020
Combined COVID-19 Dataset
sedik Ahmed, EAES Fathi, AAEL Ahmed, M Hammad
https://data.mendeley.com/datasets/3pxjb8knp7/3, 2020
2020
Detection of myocardial infarction based on novel deep transfer learning methods for urban healthcare in smart cities
A Alghamdi, M Hammad, H Ugail, A Abdel-Raheem, K Muhammad, ...
Multimedia Tools and Applications, 1-22, 2020
2020
An Effective Minimal Probing Approach With Micro-Cluster for Distance-Based Outlier Detection in Data Streams
MJ Bah, H Wang, M Hammad, F Zeshan, H Aljuaid
IEEE Access 7, 154922-154934, 2019
2019
A Novel Approach for Maternal and Fetal R- Peaks Detection
H Mohamed, I Mina, H Mohiy
IOSR Journal of VLSI and Signal Processing (IOSR-JVSP) 4 (6), 84-90, 2014
2014
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