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Omid Ghorbanzadeh
Omid Ghorbanzadeh
Institute of Advanced Research in Artificial Intelligence, Austria
Verified email at iarai.ac.at - Homepage
Title
Cited by
Cited by
Year
Evaluation of different machine learning methods and deep-learning convolutional neural networks for landslide detection
O Ghorbanzadeh, T Blaschke, K Gholamnia, SR Meena, D Tiede, J Aryal
Remote Sensing 11 (2), 196, 2019
3522019
Sustainable urban transport planning considering different stakeholder groups by an interval-AHP decision support model
O Ghorbanzadeh, S Moslem, T Blaschke, S Duleba
Sustainability 11 (1), 9, 2018
1002018
Evaluation of deep learning algorithms for national scale landslide susceptibility mapping of Iran
PTT Ngo, M Panahi, K Khosravi, O Ghorbanzadeh, N Kariminejad, ...
Geoscience Frontiers 12 (2), 505-519, 2021
942021
Flood susceptibility mapping with machine learning, multi-criteria decision analysis and ensemble using Dempster Shafer Theory
TG Nachappa, ST Piralilou, K Gholamnia, O Ghorbanzadeh, O Rahmati, ...
Journal of hydrology 590, 125275, 2020
802020
Multi-criteria risk evaluation by integrating an analytical network process approach into GIS-based sensitivity and uncertainty analyses
O Ghorbanzadeh, B Feizizadeh, T Blaschke
Geomatics, Natural Hazards and Risk 9 (1), 127-151, 2018
792018
Landslide detection using multi-scale image segmentation and different machine learning models in the higher himalayas
S Tavakkoli Piralilou, H Shahabi, B Jarihani, O Ghorbanzadeh, ...
Remote Sensing 11 (21), 2575, 2019
782019
A new GIS-based technique using an adaptive neuro-fuzzy inference system for land subsidence susceptibility mapping
O Ghorbanzadeh, T Blaschke, J Aryal, K Gholaminia
Journal of Spatial Science 65 (3), 401-418, 2020
762020
A new GIS-based data mining technique using an adaptive neuro-fuzzy inference system (ANFIS) and k-fold crossvalidation approach for land subsidence susceptibility mapping
O Ghorbanzadeh, H Rostamzadeh, T Blaschke, K Gholaminia, J Aryal
Natural Hazards, 2018
752018
Spatial prediction of wildfire susceptibility using field survey gps data and machine learning approaches
O Ghorbanzadeh, K Valizadeh Kamran, T Blaschke, J Aryal, A Naboureh, ...
Fire 2 (3), 43, 2019
682019
Analysing stakeholder consensus for a sustainable transport development decision by the fuzzy AHP and interval AHP
S Moslem, O Ghorbanzadeh, T Blaschke, S Duleba
Sustainability 11 (12), 3271, 2019
672019
Forest fire susceptibility and risk mapping using social/infrastructural vulnerability and environmental variables
O Ghorbanzadeh, T Blaschke, K Gholamnia, J Aryal
Fire 2 (3), 50, 2019
652019
An interval matrix method used to optimize the decision matrix in AHP technique for land subsidence susceptibility mapping
O Ghorbanzadeh, B Feizizadeh, T Blaschke
Environmental Earth Sciences 77 (16), 584, 2018
652018
A comparative study of statistics-based landslide susceptibility models: A case study of the region affected by the gorkha earthquake in nepal
SR Meena, O Ghorbanzadeh, T Blaschke
ISPRS international journal of geo-information 8 (2), 94, 2019
622019
An integrated approach of best-worst method (bwm) and triangular fuzzy sets for evaluating driver behavior factors related to road safety
S Moslem, M Gul, D Farooq, E Celik, O Ghorbanzadeh, T Blaschke
Mathematics 8 (3), 414, 2020
482020
UAV-based slope failure detection using deep-learning convolutional neural networks
O Ghorbanzadeh, SR Meena, T Blaschke, J Aryal
Remote Sensing 11 (17), 2046, 2019
472019
Mapping potential nature-based tourism areas by applying GIS-decision making systems in East Azerbaijan Province, Iran
O Ghorbanzadeh, S Pourmoradian, T Blaschke, B Feizizadeh
Journal of Ecotourism 18 (3), 261-283, 2019
472019
A semi-automated object-based gully networks detection using different machine learning models: a case study of Bowen catchment, Queensland, Australia
H Shahabi, B Jarihani, S Tavakkoli Piralilou, D Chittleborough, M Avand, ...
Sensors 19 (22), 4893, 2019
452019
Application of the AHP-BWM model for evaluating driver behavior factors related to road safety: A case study for Budapest
S Moslem, D Farooq, O Ghorbanzadeh, T Blaschke
Symmetry 12 (2), 243, 2020
442020
Comparisons of diverse machine learning approaches for wildfire susceptibility mapping
K Gholamnia, T Gudiyangada Nachappa, O Ghorbanzadeh, T Blaschke
Symmetry 12 (4), 604, 2020
402020
Flood susceptibility mapping using an improved analytic network process with statistical models
P Yariyan, M Avand, RA Abbaspour, A Torabi Haghighi, R Costache, ...
Geomatics, Natural Hazards and Risk 11 (1), 2282-2314, 2020
342020
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