| Support vector machine versus random forest for remote sensing image classification: A meta-analysis and systematic review M Sheykhmousa, M Mahdianpari, H Ghanbari, F Mohammadimanesh, ... IEEE Journal of Selected Topics in Applied Earth Observations and Remote …, 2020 | 641 | 2020 |
| African soil properties and nutrients mapped at 30 m spatial resolution using two-scale ensemble machine learning T Hengl, MAE Miller, J Križan, KD Shepherd, A Sila, M Kilibarda, ... Scientific reports 11 (1), 6130, 2021 | 167 | 2021 |
| Post-disaster recovery assessment with machine learning-derived land cover and land use information M Sheykhmousa, N Kerle, M Kuffer, S Ghaffarian Remote sensing 11 (10), 1174, 2019 | 52 | 2019 |
| African soil properties and nutrients mapped at 30 m spatial resolution using two-scale ensemble machine learning. Sci. Rep. 11, 6130 T Hengl, MAE Miller, J Križan, KD Shepherd, A Sila, M Kilibarda, ... | 8 | 2021 |
| Understanding post disaster recovery through assessment of land cover and land use changes using remote sensing M Sheykhmousa University of Twente, 2018 | | 2018 |
Saeid Homayouni, Ph.D., IEEE SMProfessor, INRS, Centre Eau Terre Environnment在 inrs.ca 的电子邮件经过验证
