Muhammad Hussain
Muhammad Hussain
Professor, Department of Computer Science, King Saud University
Verified email at - Homepage
Cited by
Cited by
Passive copy move image forgery detection using undecimated dyadic wavelet transform
G Muhammad, M Hussain, G Bebis
Digital investigation 9 (1), 49-57, 2012
Feature extraction and classification for EEG signals using wavelet transform and machine learning techniques
HU Amin, AS Malik, RF Ahmad, N Badruddin, N Kamel, M Hussain, ...
Australasian physical & engineering sciences in medicine 38 (1), 139-149, 2015
Image forgery detection using steerable pyramid transform and local binary pattern
G Muhammad, MH Al-Hammadi, M Hussain, G Bebis
Machine Vision and Applications 25 (4), 985-995, 2014
An automated system for epilepsy detection using EEG brain signals based on deep learning approach
IhsanUllah, M Hussain, Emad-ul-HaqQazi, H Aboalsamh
Expert Systems with Applications 107, 61-71, 2018
A comparison of SVM kernel functions for breast cancer detection
M Hussain, SK Wajid, A Elzaart, M Berbar
2011 Eighth International Conference Computer Graphics, Imaging and …, 2011
Enhancing SVM performance in intrusion detection using optimal feature subset selection based on genetic principal components
I Ahmad, M Hussain, A Alghamdi, A Alelaiwi
Neural computing and applications 24 (7-8), 1671-1682, 2014
Copy-move and splicing image forgery detection and localization techniques: a review
K Asghar, Z Habib, M Hussain
Australian Journal of Forensic Sciences 49 (3), 281-307, 2017
Passive detection of image forgery using DCT and local binary pattern
A Alahmadi, M Hussain, H Aboalsamh, G Muhammad, G Bebis, ...
Signal, Image and Video Processing 11 (1), 81-88, 2017
Gender recognition from face images with local wld descriptor
I Ullah, M Hussain, G Muhammad, H Aboalsamh, G Bebis, AM Mirza
2012 19th International Conference on Systems, Signals and Image Processing …, 2012
Accurate and robust localization of duplicated region in copy–move image forgery
M Jaberi, G Bebis, M Hussain, G Muhammad
Machine vision and applications 25 (2), 451-475, 2014
Blind copy move image forgery detection using dyadic undecimated wavelet transform
G Muhammad, M Hussain, K Khawaji, G Bebis
2011 17th International Conference on Digital Signal Processing (DSP), 1-6, 2011
P300 correlates with learning & memory abilities and fluid intelligence
HU Amin, AS Malik, N Kamel, WT Chooi, M Hussain
Journal of neuroengineering and rehabilitation 12 (1), 87, 2015
Efficient and feature-preserving triangular mesh decimation.
M Hussain, Y Okada, K Niijima
WSCG, 167-174, 2004
Splicing Image Forgery Detection Based on DCT and Local Binary Pattern
AA Alahmadi, M Hussain, H Aboalsamh, G Muhammad, G Bebis
Global Conference on Signal and Information Processing (GlobalSIP), 2013 …, 2013
Electroencephalogram (EEG)-based computer-aided technique to diagnose major depressive disorder (MDD)
W Mumtaz, L Xia, SSA Ali, MAM Yasin, M Hussain, AS Malik
Biomedical Signal Processing and Control 31, 108-115, 2017
Optimized intrusion detection mechanism using soft computing techniques
I Ahmad, A Abdullah, A Alghamdi, M Hussain
Telecommunication Systems 52 (4), 2187-2195, 2013
A comparison of different Gabor feature extraction approaches for mass classification in mammography
S Khan, M Hussain, H Aboalsamh, G Bebis
Multimedia Tools and Applications 76 (1), 33-57, 2017
Copy-move forgery detection using dyadic wavelet transform
N Muhammad, M Hussain, G Muhammad, G Bebis
2011 Eighth International Conference Computer Graphics, Imaging and …, 2011
Comparison of statistical, LBP, and multi-resolution analysis features for breast mass classification
YA Reyad, MA Berbar, M Hussain
Journal of medical systems 38 (9), 100, 2014
Image forgery detection using multi-resolution Weber local descriptors
M Hussain, G Muhammad, SQ Saleh, AM Mirza, G Bebis
Eurocon 2013, 1570-1577, 2013
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