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 | 847 | 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 | 207 | 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 | 58 | 2019 |
African soil properties and nutrients mapped at 30m spatial resolution using two-scale ensemble machine learning, Sci. Rep., 11, 6130 T Hengl, MAE Miller, J Križan, KD Shepherd, A Sila, M Kilibarda, ... | 15 | 2021 |
Understanding post disaster recovery through assessment of land cover and land use changes using remote sensing M Sheykhmousa University of Twente, 2018 | | 2018 |