| Land cover classification from fused DSM and UAV images using convolutional neural networks HAH Al-Najjar, B Kalantar, B Pradhan, V Saeidi, AA Halin, N Ueda, ... | 201 | 2019 |
| Optimizing ANN models with PSO for predicting short building seismic response H Nguyen, H Moayedi, LK Foong, HAH Al Najjar, WAW Jusoh, ... Engineering with Computers, 1-15, 2019 | 161 | 2019 |
| Spatial landslide susceptibility assessment using machine learning techniques assisted by additional data created with generative adversarial networks HAH Al-Najjar, B Pradhan Geoscience Frontiers 12 (2), 625-637, 2021 | 152 | 2021 |
| A novel method using explainable artificial intelligence (XAI)-based Shapley Additive Explanations for spatial landslide prediction using Time-Series SAR dataset HAH Al-Najjar, B Pradhan, G Beydoun, R Sarkar, HJ Park, A Alamri Gondwana Research 123, 107-124, 2023 | 104 | 2023 |
| Optimized conditioning factors using machine learning techniques for groundwater potential mapping B Kalantar, HAH Al-Najjar, B Pradhan, V Saeidi, AA Halin, N Ueda, ... Water 11 (9), 1909, 2019 | 81 | 2019 |
| Assessment of convolutional neural network architectures for earthquake-induced building damage detection based on pre-and post-event orthophoto images B Kalantar, N Ueda, HAH Al-Najjar, AA Halin Remote Sensing 12 (21), 3529, 2020 | 60 | 2020 |
| Unseen land cover classification from high-resolution orthophotos using integration of zero-shot learning and convolutional neural networks B Pradhan, HAH Al-Najjar, MI Sameen, I Tsang, AM Alamri | 60 | 2020 |
| Landslide susceptibility modeling: an integrated novel method based on machine learning feature transformation HAH Al-Najjar, B Pradhan, B Kalantar, MI Sameen, M Santosh, A Alamri Remote Sensing 13 (16), 3281, 2021 | 50 | 2021 |
| Maximum likelihood for land-use/land-cover mapping and change detection using Landsat satellite images: A case study “South of Johor” HAAR Abd, HAH Al-Najjar International Journal of computational Engineering research (IJCER) IJCER …, 2013 | 50 | 2013 |
| Conditioning factor determination for mapping and prediction of landslide susceptibility using machine learning algorithms HAH Al-Najjar, B Kalantar, B Pradhan, V Saeidi Earth resources and environmental remote sensing/GIS applications X 11156 …, 2019 | 47 | 2019 |
| A new integrated approach for landslide data balancing and spatial prediction based on generative adversarial networks (GAN) HAH Al-Najjar, B Pradhan, R Sarkar, G Beydoun, A Alamri Remote Sensing 13 (19), 4011, 2021 | 40 | 2021 |
| A meta-learning approach of optimisation for spatial prediction of landslides B Pradhan, MI Sameen, HAH Al-Najjar, D Sheng, AM Alamri, HJ Park Remote Sensing 13 (22), 4521, 2021 | 34 | 2021 |
| Conditioning factors determination for landslide susceptibility mapping using support vector machine learning B Kalantar, N Ueda, US Lay, HAH Al-Najjar, AA Halin IGARSS 2019-2019 IEEE International Geoscience and Remote Sensing Symposium …, 2019 | 34 | 2019 |
| Landslide detection using a saliency feature enhancement technique from LiDAR-derived DEM and orthophotos B Pradhan, HAH Al-Najjar, MI Sameen, MR Mezaal, AM Alamri Ieee Access 8, 121942-121954, 2020 | 26 | 2020 |
| An evaluation of landslide susceptibility mapping using remote sensing data and machine learning algorithms in Iran B Kalantar, N Ueda, HAH Al-Najjar, MBA Gibril, US Lay, A Motevalli ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information …, 2019 | 12 | 2019 |
| Uav and lidar image registration: A surf-based approach for ground control points selection B Kalantar, N Ueda, HAH Al-Najjar, H Moayedi, AA Halin, S Mansor The International Archives of the Photogrammetry, Remote Sensing and Spatial …, 2019 | 11 | 2019 |
| Object-oriented approach for urbanization growth by using remote sensing and gis techniques: a case study in Hilla city, Babylon Governorate, Iraq AS Mahmoud, B Kalantar, HAH Al-Najjar, H Moayedi, AA Halin, S Mansor Geospatial Technology and Smart Cities: ICT, Geoscience Modeling, GIS and …, 2021 | 9 | 2021 |
| Optimized conditioning factors using machine learning techniques for groundwater potential mapping. Water 11 (9): 1909 B Kalantar, HAH Al-Najjar, B Pradhan, V Saeidi, AA Halin, N Ueda, ... | 9 | 2019 |
| Unseen land cover classification from high-resolution orthophotos using integration of zero-shot learning and convolutional neural networks. Remote Sens 12: 1676 B Pradhan, HAH Al-Najjar, MI Sameen, I Tsang, AM Alamri | 8 | 2020 |
| A framework for multiple moving objects detection in aerial videos B Kalantar, AA Halin, HAH Al-Najjar, S Mansor, JL van Genderen, ... Spatial Modeling in GIS and R for Earth and Environmental Sciences, 573-588, 2019 | 7 | 2019 |