Mahmoud Salah
Mahmoud Salah
Faculty of Engineering Shoubra - Surveying Engineering Department
Verified email at - Homepage
Cited by
Cited by
Evaluation of the self‐organizing map classifier for building detection from lidar data and multispectral aerial images
M Salah, J Trinder, A Shaker
Journal of Spatial Science 54 (2), 15-34, 2009
Prevalence and comorbidity of depression, anxiety and obsessive compulsive disorders among Saudi secondary school girls, Taif Area, KSA
ARCHIVES OF IRANIAN MEDICINE 18 (4), 234-238, 2015
Aerial images and LiDAR data fusion for disaster change detection
J Trinder, M Salah
ISPRS Ann. Photogramm. Remote Sens. Spat. Inf. Sci 1, 227-232, 2012
A survey of modern classification techniques in remote sensing for improved image classification
M Salah
Journal of Geomatics 11 (1), 21, 2017
Assessment of proposed approaches for bathymetry calculations using multispectral satellite images in shallow coastal/lake areas: a comparison of five models
H Mohamed, M Salah, K Nadaoka, M Zahran
Arabian Journal of Geosciences 10 (2), 42, 2017
Disaster change detection using airborne LiDAR
J Trinder, M Salah
Proceedings of the, 2011
Integrating multiple classifiers with fuzzy majority voting for improved land cover classification
M Salah, JC Trinder, A Shaker, M Hamed, A Elsagheer
Proc. Int. Arch. of Photogramm. Remote Sens, 2010
Aerial images and lidar data fusion for automatic feature extraction using the self-organizing map (som) classifier
M Salah, J Trinder, A Shaker, M Hamed, A Elsagheer
proceedings of the 38th ISPRS Congress-XXXVIII, Part 3/W8, 1-2, 2009
Performance evaluation of classification trees for building detection from aerial images and LiDAR data: a comparison of classification trees models
M Salah, JC Trinder, A Shaker
International journal of remote sensing 32 (20), 5757-5783, 2011
Support Vector Machines: Optimization and validation for land cover mapping using aerial images and lidar data
JC Trinder, M Salah
Laser 1 (1.064), 1.047, 2011
Support vector machines based filtering of lidar data: a grid based method
M Salah, J Trinder
Sensitivity of pixel-based classifiers to training sample size in cas of high resolution satellite imagery
ML Doma, MS Gomaa, RA Amer
Journal of Geomatics 9 (1), 53-58, 2015
Accuracy of 3D models derived from aerial laser scanning and aerial ortho-imagery
H Park, M Salah, S Lim
Survey Review 43 (320), 109-122, 2011
Airborne Lidar as a Tool for Disaster Monitoring and Management
JC Trinder, M Salah
Proceedings of the GeoInformation for Disaster Management, Antalya, Turkey, 3-8, 2011
Assessment of spread range of urban development in the west delta by utilizing high resolution satellite images
A Shehaby, M Semary, M Salah, SM Ibrahim
J. Civ. Eng. Res 2 (6), 57-63, 2012
Towards Automatic Feature Extraction from High Resolution Digital Imagery and Lidar Data for GIS Applications
M Salah
Benha University, 2010
A note on Riemann zeta function
JY Salah
IOSR Journal of Engineering (IOSRJEN) 6 (2), 7-16, 2016
Determination of Shallow Water Depths using Inverse Probability Weighted Interpolation: a hybrid system-based method
M Salah
International Journal of Geoinformatics 12 (1), 45-55, 2016
Combining statistical and neural classifiers using Dempster-Shafer theory of evidence for improved building detection
J Trinder, M Salah, A Shaker, M Hamed, A Elsagheer
Proc. 15th Australas. Remote Sens. Photogramm. Conf, 13-16, 2010
Fuzzy ARTMAP neural networks for automatic feature extraction from aerial images and lidar data
M Salah, J Trinder
Proc. GeoComputation 2009 conference, UNSW Sydney, Australia 30, 2009
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