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Shahriar Shah Heydari
Shahriar Shah Heydari
postdoc Scholar, Colorado State University
Bestätigte E-Mail-Adresse bei colostate.edu
Titel
Zitiert von
Zitiert von
Jahr
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
1692018
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
692019
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
92023
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
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