Muhammad Hussain
Muhammad Hussain
Professor, Department of Computer Science, King Saud University
Verified email at - Homepage
TitleCited byYear
Passive copy move image forgery detection using undecimated dyadic wavelet transform
G Muhammad, M Hussain, G Bebis
Digital Investigation 9 (1), 49-57, 2012
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
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
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
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
Efficient and feature-preserving triangular mesh decimation.
M Hussain, Y Okada, K Niijima
WSCG, 167-174, 2004
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
Blind copy move image forgery detection using dyadic undecimated wavelet transform
G Muhammad, M Hussain, K Khawaji, G Bebis
Digital Signal Processing (DSP), 2011 17th International Conference on, 1-6, 2011
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
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
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
Copy-Move Forgery Detection Using Dyadic Wavelet Transform
N Muhammad, M Hussain, G Muhammad, G Bebis
Computer Graphics, Imaging and Visualization (CGIV), 2011 Eighth …, 2011
Optimized intrusion detection mechanism using soft computing techniques
I Ahmad, A Abdullah, A Alghamdi, M Hussain
Telecommunication Systems 52 (4), 2187-2195, 2013
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
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
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
Image forgery detection using multi-resolution Weber local descriptors
M Hussain, G Muhammad, SQ Saleh, AM Mirza, G Bebis
EUROCON, 2013 IEEE, 1570-1577, 2013
The dyadic lifting schemes and the denoising of digital images
TA Türüki, M Hussain, K Niijima, S Takano
International Journal of Wavelets, Multiresolution and Information …, 2008
Effective extraction of Gabor features for false positive reduction and mass classification in mammography
M Hussain, S Khan, G Muhammad, I Ahmed, G Bebis
Appl. Math 8 (1L), 397-412, 2014
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