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Omid Ghorbanzadeh
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2020 – today
- 2024
- [j27]Omid Ghorbanzadeh
, Hejar Shahabi
Contrastive Self-Supervised Learning for Globally Distributed Landslide Detection. IEEE Access 12: 118453-118466 (2024) - 2023
- [j26]Ratiranjan Jena
Explainable Artificial Intelligence (XAI) Model for Earthquake Spatial Probability Assessment in Arabian Peninsula. Remote. Sens. 15(9): 2248 (2023) - [j25]Ratiranjan Jena, Abdallah Shanableh
An Integration of Deep Learning and Transfer Learning for Earthquake-Risk Assessment in the Eurasian Region. Remote. Sens. 15(15): 3759 (2023) - 2022
- [j24]Sepideh Tavakkoli Piralilou, Golzar Einali, Omid Ghorbanzadeh
A Google Earth Engine Approach for Wildfire Susceptibility Prediction Fusion with Remote Sensing Data of Different Spatial Resolutions. Remote. Sens. 14(3): 672 (2022) - [j23]Soodabeh Namdari
Time Series of Remote Sensing Data for Interaction Analysis of the Vegetation Coverage and Dust Activity in the Middle East. Remote. Sens. 14(13): 2963 (2022) - [j22]Omid Ghorbanzadeh
Mapping Dwellings in IDP/Refugee Settlements Using Deep Learning. Remote. Sens. 14(24): 6382 (2022) - [j21]Bilal Aslam
Evaluation of Different Landslide Susceptibility Models for a Local Scale in the Chitral District, Northern Pakistan. Sensors 22(9): 3107 (2022) - [j20]Omid Ghorbanzadeh
The Outcome of the 2022 Landslide4Sense Competition: Advanced Landslide Detection From Multisource Satellite Imagery. IEEE J. Sel. Top. Appl. Earth Obs. Remote. Sens. 15: 9927-9942 (2022) - [j19]Omid Ghorbanzadeh
Landslide4Sense: Reference Benchmark Data and Deep Learning Models for Landslide Detection. IEEE Trans. Geosci. Remote. Sens. 60: 1-17 (2022) - [c3]Hejar Shahabi, Omid Ghorbanzadeh:
Model-Centric vs Data-Centric Deep Learning Approaches for Landslide Detection. CDCEO@IJCAI 2022: 44-49 - [c2]Pedram Ghamisi, Omid Ghorbanzadeh, Yonghao Xu, Pedro Herruzo, David P. Kreil, Michael Kopp, Sepp Hochreiter:
The Landslide4Sense Competition 2022. CDCEO@IJCAI 2022: 91 - [i2]Omid Ghorbanzadeh, Yonghao Xu, Pedram Ghamisi, Michael Kopp, David P. Kreil:
Landslide4Sense: Reference Benchmark Data and Deep Learning Models for Landslide Detection. CoRR abs/2206.00515 (2022) - [i1]Omid Ghorbanzadeh, Yonghao Xu, Hengwei Zhao, Junjue Wang, Yanfei Zhong, Dong Zhao, Qi Zang, Shuang Wang, Fahong Zhang, Yilei Shi, Xiao Xiang Zhu, Lin Bai, Weile Li
The Outcome of the 2022 Landslide4Sense Competition: Advanced Landslide Detection from Multi-Source Satellite Imagery. CoRR abs/2209.02556 (2022) - 2021
- [j18]Hejar Shahabi
Unsupervised Deep Learning for Landslide Detection from Multispectral Sentinel-2 Imagery. Remote. Sens. 13(22): 4698 (2021) - [j17]Omid Ghorbanzadeh
Landslide Mapping Using Two Main Deep-Learning Convolution Neural Network Streams Combined by the Dempster-Shafer Model. IEEE J. Sel. Top. Appl. Earth Obs. Remote. Sens. 14: 452-463 (2021) - 2020
- [j16]Ahsen Maqsoom
A GIS-based DRASTIC Model and an Adjusted DRASTIC Model (DRASTICA) for Groundwater Susceptibility Assessment along the China-Pakistan Economic Corridor (CPEC) Route. ISPRS Int. J. Geo Inf. 9(5): 332 (2020) - [j15]Meisam Moharrami
National-Scale Landslide Susceptibility Mapping in Austria Using Fuzzy Best-Worst Multi-Criteria Decision-Making. ISPRS Int. J. Geo Inf. 9(6): 393 (2020) - [j14]Omid Ghorbanzadeh
An Application of Sentinel-1, Sentinel-2, and GNSS Data for Landslide Susceptibility Mapping. ISPRS Int. J. Geo Inf. 9(10): 561 (2020) - [j13]Saeedeh Eskandari
Mapping Land Cover and Tree Canopy Cover in Zagros Forests of Iran: Application of Sentinel-2, Google Earth, and Field Data. Remote. Sens. 12(12): 1912 (2020) - [j12]Thimmaiah Gudiyangada Nachappa
Multi-Hazard Exposure Mapping Using Machine Learning for the State of Salzburg, Austria. Remote. Sens. 12(17): 2757 (2020) - [j11]Sarbast Moslem
Application of the AHP-BWM Model for Evaluating Driver Behavior Factors Related to Road Safety: A Case Study for Budapest. Symmetry 12(2): 243 (2020) - [j10]Peyman Yariyan, Mohammadtaghi Avand
Earthquake Vulnerability Mapping Using Different Hybrid Models. Symmetry 12(3): 405 (2020) - [j9]Khalil Gholamnia
Comparisons of Diverse Machine Learning Approaches for Wildfire Susceptibility Mapping. Symmetry 12(4): 604 (2020)
2010 – 2019
- 2019
- [j8]Sansar Raj Meena
A Comparative Study of Statistics-Based Landslide Susceptibility Models: A Case Study of the Region Affected by the Gorkha Earthquake in Nepal. ISPRS Int. J. Geo Inf. 8(2): 94 (2019) - [j7]Amin Naboureh
Traffic Accident Spatial Simulation Modeling for Planning of Road Emergency Services. ISPRS Int. J. Geo Inf. 8(9): 371 (2019) - [j6]Omid Ghorbanzadeh
Evaluation of Different Machine Learning Methods and Deep-Learning Convolutional Neural Networks for Landslide Detection. Remote. Sens. 11(2): 196 (2019) - [j5]Omid Ghorbanzadeh
UAV-Based Slope Failure Detection Using Deep-Learning Convolutional Neural Networks. Remote. Sens. 11(17): 2046 (2019) - [j4]Sepideh Tavakkoli Piralilou, Hejar Shahabi
Landslide Detection Using Multi-Scale Image Segmentation and Different Machine Learning Models in the Higher Himalayas. Remote. Sens. 11(21): 2575 (2019) - [j3]Omid Rahmati
Spatial Modeling of Snow Avalanche Using Machine Learning Models and Geo-Environmental Factors: Comparison of Effectiveness in Two Mountain Regions. Remote. Sens. 11(24): 2995 (2019) - [j2]Alireza Arabameri
Application of Probabilistic and Machine Learning Models for Groundwater Potentiality Mapping in Damghan Sedimentary Plain, Iran. Remote. Sens. 11(24): 3015 (2019) - [j1]Hejar Shahabi
A Semi-Automated Object-Based Gully Networks Detection Using Different Machine Learning Models: A Case Study of Bowen Catchment, Queensland, Australia. Sensors 19(22): 4893 (2019) - [c1]Omid Ghorbanzadeh
Optimizing Sample Patches Selection of CNN to Improve the mIOU on Landslide Detection. GISTAM 2019: 33-40
Coauthor Index
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last updated on 2024-10-07 21:15 CEST by the dblp team
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