Machine learning applications for earth observation DJ Lary, GK Zewdie, X Liu, D Wu, E Levetin, RJ Allee, N Malakar, ... Earth observation open science and innovation 165, 2018 | 81 | 2018 |
Data‐driven forecasting of low‐latitude ionospheric total electron content using the random forest and LSTM machine learning methods GK Zewdie, C Valladares, MB Cohen, DJ Lary, D Ramani, GM Tsidu Space Weather 19 (6), e2020SW002639, 2021 | 35 | 2021 |
Applying Deep Neural Networks and Ensemble Machine Learning Methods to Forecast Airborne Ambrosia Pollen GK Zewdie, DJ Lary, E Levetin, GF Garuma International journal of environmental research and public health 16 (11), 1992, 2019 | 29 | 2019 |
Using machine learning to estimate atmospheric Ambrosia pollen concentrations in Tulsa, OK X Liu, D Wu, GK Zewdie, L Wijerante, CI Timms, A Riley, E Levetin, ... Environmental Health Insights 11, 1178630217699399, 2017 | 28 | 2017 |
Estimating the daily pollen concentration in the atmosphere using machine learning and NEXRAD weather radar data GK Zewdie, DJ Lary, X Liu, D Wu, E Levetin Environmental monitoring and assessment 191, 1-9, 2019 | 27 | 2019 |
Using machine learning to understand the temporal morphology of the PM2.5 annual cycle in East Asia D Wu, DJ Lary, GK Zewdie, X Liu Environmental monitoring and assessment 191 (Suppl 2), 272, 2019 | 17 | 2019 |
Applying machine learning to forecast daily Ambrosia pollen using environmental and NEXRAD parameters GK Zewdie, X Liu, D Wu, DJ Lary, E Levetin Environmental monitoring and assessment 191, 1-11, 2019 | 14 | 2019 |
Insights Into the Morphology of the East Asia PM2.5 Annual Cycle Provided by Machine Learning D Wu, GK Zewdie, X Liu, MA Kneen, DJ Lary Environmental health insights 11, 1178630217699611, 2017 | 13 | 2017 |
High-resolution coherent backscatter interferometric radar images of equatorial spread F using Capon's method FS Rodrigues, ER De Paula, GK Zewdie Annales Geophysicae 35 (3), 393-402, 2017 | 7 | 2017 |
Applying machine learning to estimate allergic pollen using environmental, land surface and NEXRAD radar parameters G Zewdie, DJ Lary AGU Fall Meeting Abstracts 2018, A23M-3078, 2018 | 5 | 2018 |
Machine learning, big data, and spatial tools: A combination to reveal complex facts that impact environmental health DJ Lary, LOH Wijeratne, GK Zewdie, D Kiv, D Wu, FS Faruque, S Talebi, ... Geospatial Technology for Human Well-Being and Health, 219-241, 2021 | 2 | 2021 |
TOMOGRAPHIC IMAGING OF IONOSPHERIC ELECTRON DENSITY OVER ETHIOPIA USING GROUND BASED GPS RECEIVERS GK Zewdie, GM Tsidu Addis Ababa University, 2012 | 2 | 2012 |
An HF Receiving Array for Radio Imaging of Stimulated Electromagnetic Emissions and Radar Imaging of the Ionosphere B Isham, T Bullett, B Gustavsson, E Polisensky, G Zewdie, V Belyey, ... 44th COSPAR Scientific Assembly. Held 16-24 July 44, 1006, 2022 | | 2022 |
3D Machine Learning for Ionospheric Forecasting with Synthetic Data and Data-Model Fusion L Smith, G Zewdie, M Cohen, J Huba, S Dutta, B Bristow, Y Morton AGU Fall Meeting Abstracts 2021, SA45C-2238, 2021 | | 2021 |
Advancement in Airborne Particulate Estimation Using Machine Learning LOH Wijeratne, GK Zewdie, D Kiv, A Aker, DJ Lary, S Talebi, X Yu, ... Geospatial Technology for Human Well-Being and Health, 243-263, 2021 | | 2021 |
Forecasting of Ionospheric real GPS TEC and SAMI3 model output parameters using the LSTM deep recurrent neural network G Zewdie, M Cohen AGU Fall Meeting Abstracts 2020, NG004-0019, 2020 | | 2020 |
Nowcasting of Ionospheric Total Electron Content Using the Random Forest and Deep Neural Network Machine Learning Methods G Zewdie, M Cohen, CE Valladares, DJ Lary AGU Fall Meeting Abstracts 2019, NG31A-0849, 2019 | | 2019 |
Using a Comprehensive Characterization of the Physical Environment and Machine Learning to Forecast the Abundance of Airborne Pollen GK Zewdie The University of Texas at Dallas, 2019 | | 2019 |
Applying machine learning and deep learning to forecast allergic pollen using environmental, land surface and NEXRAD radar parameters GK Zewdie, DJ Lary, X Liu, D Wu, E Levetin AGU poster, 2018 | | 2018 |
Insights into the morphology of the East Asia PM2.5 annual cycle provided by machine learning. WDJ Wu DaJi, GK Zewdie, LX Liu Xun, MA Kneen, DJ Lary | | 2017 |