Omid Ghorbanzadeh

About Omid Ghorbanzadeh

Omid Ghorbanzadeh, With an exceptional h-index of 38 and a recent h-index of 38 (since 2020), a distinguished researcher at Universität Salzburg, specializes in the field of AI4RS.

His recent articles reflect a diverse array of research interests and contributions to the field:

Transformer-based semantic segmentation for large-scale building footprint extraction from very-high resolution satellite images

A Comparison of SimCLR and SwAV Contrastive Self-Supervised Learning Models For Landslide Detection

Identifying Influential Spatial Drivers of Forest Fires through Geographically and Temporally Weighted Regression Coupled with a Continuous Invasive Weed Optimization Algorithm

The application of ResU-net and OBIA for landslide detection from multi-temporal sentinel-2 images

Earthquake spatial probability and hazard estimation using various explainable AI (XAI) models at the Arabian Peninsula

An integration of deep learning and transfer learning for earthquake-risk assessment in the Eurasian region

Explainable artificial intelligence (XAI) model for earthquake spatial probability assessment in Arabian peninsula

Ensembling of decision trees, KNN, and logistic regression with soft-voting method for wildfire susceptibility mapping

Omid Ghorbanzadeh Information

University

Position

PhD Researcher in Geoinformatics Techno Z_GIS

Citations(all)

4236

Citations(since 2020)

4202

Cited By

983

hIndex(all)

38

hIndex(since 2020)

38

i10Index(all)

57

i10Index(since 2020)

57

Email

University Profile Page

Google Scholar

Omid Ghorbanzadeh Skills & Research Interests

AI4RS

Top articles of Omid Ghorbanzadeh

Transformer-based semantic segmentation for large-scale building footprint extraction from very-high resolution satellite images

Advances in Space Research

2024/5/15

A Comparison of SimCLR and SwAV Contrastive Self-Supervised Learning Models For Landslide Detection

2024/3/7

Omid Ghorbanzadeh
Omid Ghorbanzadeh

H-Index: 18

Identifying Influential Spatial Drivers of Forest Fires through Geographically and Temporally Weighted Regression Coupled with a Continuous Invasive Weed Optimization Algorithm

Fire

2024/1/18

Parham Pahlavani
Parham Pahlavani

H-Index: 9

Omid Ghorbanzadeh
Omid Ghorbanzadeh

H-Index: 18

The application of ResU-net and OBIA for landslide detection from multi-temporal sentinel-2 images

Big Earth Data

2023/10/2

Omid Ghorbanzadeh
Omid Ghorbanzadeh

H-Index: 18

Khalil Gholamnia
Khalil Gholamnia

H-Index: 7

Earthquake spatial probability and hazard estimation using various explainable AI (XAI) models at the Arabian Peninsula

Remote Sensing Applications: Society and Environment

2023/8/1

An integration of deep learning and transfer learning for earthquake-risk assessment in the Eurasian region

Remote Sensing

2023/7/28

Explainable artificial intelligence (XAI) model for earthquake spatial probability assessment in Arabian peninsula

Remote Sensing

2023/4/24

Ensembling of decision trees, KNN, and logistic regression with soft-voting method for wildfire susceptibility mapping

ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences

2023/1/14

How the recursive feature elimination affects the SVM and RF for wildfire modeling? A mountainous case study area

EGUsphere

2023/1/10

Parham Pahlavani
Parham Pahlavani

H-Index: 9

Omid Ghorbanzadeh
Omid Ghorbanzadeh

H-Index: 18

Mapping Dwellings in IDP/Refugee Settlements Using Deep Learning

Remote Sensing

2022/12/16

The outcome of the 2022 landslide4sense competition: Advanced landslide detection from multisource satellite imagery

IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing

2022/11/9

Fire vulnerability of Hyrcanian forests (FVHF): A conceptual framework for an enhanced forest fire risk management in northern Iran

Intercontinental Geoinformation Days

2022/9/20

Omid Ghorbanzadeh
Omid Ghorbanzadeh

H-Index: 18

Mahmoud Daneshvar Kakhki
Mahmoud Daneshvar Kakhki

H-Index: 5

Time series of remote sensing data for interaction analysis of the vegetation coverage and dust activity in the middle east

Remote Sensing

2022/6/21

Landslide4Sense: Reference Benchmark Data and Deep Learning Models for Landslide Detection

arXiv preprint arXiv:2206.00515

2022/6/1

Evaluation of different landslide susceptibility models for a local scale in the Chitral District, Northern Pakistan

Sensors

2022/4/19

Flood susceptibility mapping using meta-heuristic algorithms

Geomatics, Natural Hazards and Risk

2022/4/11

Landslide detection using deep learning and object-based image analysis

Landslides

2022/4

Omid Ghorbanzadeh
Omid Ghorbanzadeh

H-Index: 18

Thomas Blaschke
Thomas Blaschke

H-Index: 49

Rapid mapping of landslides from sentinel-2 data using unsupervised deep learning

2022/3/7

A Google Earth Engine approach for wildfire susceptibility prediction fusion with remote sensing data of different spatial resolutions

Remote sensing

2022/1/30

The Landslide4Sense Competition 2022.

2022

See List of Professors in Omid Ghorbanzadeh University(Universität Salzburg)

Co-Authors

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