Performance comparison of an LSTM-based deep learning model versus conventional machine learning algorithms for streamflow forecasting M Rahimzad, A Moghaddam Nia, H Zolfonoon, J Soltani, ... Water Resources Management 35 (12), 4167-4187, 2021 | 103 | 2021 |
Danandeh Mehr A, Kwon HH (2021) Performance comparison of an LSTM-based deep learning model versus conventional machine learning algorithms for streamflow forecasting M Rahimzad, A Moghaddam Nia, H Zolfonoon, J Soltani Water Resources Management 35 (12), 4167-4187, 0 | 45 | |
Unsupervised deep learning for landslide detection from multispectral sentinel-2 imagery H Shahabi, M Rahimzad, S Tavakkoli Piralilou, O Ghorbanzadeh, ... Remote Sensing 13 (22), 4698, 2021 | 31 | 2021 |
An efficient multi-sensor remote sensing image clustering in urban areas via boosted convolutional autoencoder (BCAE) M Rahimzad, S Homayouni, A Alizadeh Naeini, S Nadi Remote Sensing 13 (13), 2501, 2021 | 16 | 2021 |
Rapid mapping of landslides from sentinel-2 data using unsupervised deep learning H Shahabi, M Rahimzad, O Ghorbanzadeh, ST Piralilou, T Blaschke, ... 2022 IEEE Mediterranean and Middle-East Geoscience and Remote Sensing …, 2022 | 4 | 2022 |
Clustering of Remotely-Sensed Data Using Autoencoder-Driven Features M Rahimzad University of Isfahan (http://thesisdl.ui.ac.ir/Forms/Public/Details.aspx?Id …, 2019 | | 2019 |
Prediction of PM10 concentration in Tehran using neural network and MODIS images S Beheshtifar, M Rahimzad The 4th International Conference on Environmental Engineering with a focus …, 2018 | | 2018 |