Effect of classifier selection, reference sample size, reference class distribution and scene heterogeneity in per-pixel classification accuracy using 26 Landsat sites SS Heydari, G Mountrakis Remote Sensing of Environment 204, 648-658, 2018 | 170 | 2018 |
Meta-analysis of deep neural networks in remote sensing: A comparative study of mono-temporal classification to support vector machines SS Heydari, G Mountrakis ISPRS journal of photogrammetry and remote sensing 152, 192-210, 2019 | 69 | 2019 |
Harvesting the Landsat archive for land cover land use classification using deep neural networks: Comparison with traditional classifiers and multi-sensor benefits G Mountrakis, SS Heydari ISPRS journal of photogrammetry and remote sensing 200, 106-119, 2023 | 9 | 2023 |
Continental US Land Cover Mapping using Deep Neural Networks, Landsat Time-series Observations and Large Reference Datasets G Mountrakis, S Shah Heydari AGU Fall Meeting Abstracts 2021, B31C-01, 2021 | | 2021 |
Large Area Land Cover Mapping Using Deep Neural Networks and Landsat Time-Series Observations SS Heydari State University of New York College of Environmental Science and Forestry, 2021 | | 2021 |
Large Area Land Cover Mapping Using Deep Neural Networks and Landsat Time-Series Observations S Shah Heydari | | 2021 |
Optimizing Spatial-Spectral-Temporal Neural Network Models for Large-Scale Landcover Classification Based on Landsat Data Archive S Shah Heydari, G Mountrakis AGU Fall Meeting Abstracts 2020, IN007-06, 2020 | | 2020 |
Alternate solutions in mixing energy tax/subsidy and emission control policies SS Heydari, N Vestergaard IME Working Paper, 2015 | | 2015 |
Estimating the Effect of Energy Policies on Residential Energy Consumption in Selected EU Countries S Shah-Heydari Syddansk Universitet, 2014 | | 2014 |
Interacting effects of socio-political and environmental factors on rangeland dynamics in the Altai Mountains in Central Asia G Mountrakis, J Gibbs, L Iegorova, M Paltsyn, S Heydari | | |