Mohammad Kakooei

Postdoc at Data Science and AI

Mohammad Kakooei received the B.S., M.Sc., and Ph.D. degrees in electronic engineering from Shahid Beheshti University (SBU), Iran University of Science and Technology (IUST), and Babol Noshirvani University of Technology (BNUT), in 2011, 2014, and 2020, respectively. He conducted some research at the urban planning group of the Geoinformatics Division of KTH (Royal Institute of Technology), Stockholm in 2018 as a visiting PHD student. He became a postdoc researcher with the Department of Computer and Electrical Engineering, BNUT in 2020. He is currently a Researcher with the Department of Data Science and Artificial Intelligence, Chalmers University of Technology, Gothenburg, Sweden. His research interests include image processing, machine learning, remote sensing, earth observation, and data mining applications.

Source: chalmers.se
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Showing 7 publications

2024

Increasing the confidence of predictive uncertainty: earth observations and deep learning for poverty estimation

Mohammad Kakooei, Adel Daoud
IEEE Transactions on Geoscience and Remote Sensing. Vol. In Press
Journal article
2023

Spatial-Temporal analysis of urban environmental variables using building height features

Mohammad Kakooei, Yasser Baleghi
Urban Climate. Vol. 52
Journal article
2023

Wetland Mapping in Great Lakes Using Sentinel-1/2 Time-Series Imagery and DEM Data in Google Earth Engine

Farzane Mohseni, Meisam Amani, Pegah Mohammadpour et al
Remote Sensing. Vol. 15 (14)
Journal article
2023

Satellite-Based Estimation of Soil Moisture Content in Croplands: A Case Study in Golestan Province, North of Iran

Soraya Bandak, Seyed Ali Reza Movahedi Naeini, Chooghi Bairam Komaki et al
Remote Sensing. Vol. 15 (8)
Journal article
2023

Time Series of Satellite Imagery Improve Deep Learning Estimates of Neighborhood-Level Poverty in Africa

Markus Pettersson, Mohammad Kakooei, Julia Ortheden et al
IJCAI International Joint Conference on Artificial Intelligence. Vol. 2023-August, p. 6165-6173
Paper in proceeding
2022

Forty Years of Wetland Status and Trends Analyses in the Great Lakes Using Landsat Archive Imagery and Google Earth Engine

Meisam Amani, Mohammad Kakooei, Arsalan Ghorbanian et al
Remote Sensing. Vol. 14 (15)
Journal article
2022

ELULC‐10, a 10 m European Land Use and Land Cover Map Using Sentinel and Landsat Data in Google Earth Engine

S. Mohammad Mirmazloumi, Mohammad Kakooei, Farzane Mohseni et al
Remote Sensing. Vol. 14 (13)
Journal article

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