M. Sadeghi

发表

PERSIANN-CNN: Precipitation Estimation from Remotely Sensed Information Using Artificial Neural Networks–Convolutional Neural Networks

Kuolin Hsu, Soroosh Sorooshian, Ata Akbari Asanjan, 2019, Journal of Hydrometeorology.

Investigation of Corrosion Behavior of Drain Pipes of Process Compressors in Direct Reduction Unit.

M. Sadeghi, S. Abdollahi, 2020 .

Analysis, modeling and optimization of regional development in Sistan & Balochestan combining labor market, shift-share and genetic algorithm models

M. Sadeghi, M. Shokouhi, R. Asadi, 2013 .

Acceptability of picture archiving and communication system (PACS) among hospital healthcare personnel based on a unified theory of acceptance and use of technology

M. Ahmadi, M. Sadeghi, A. Sheikhtaheri, 2017, Electronic physician.

PERSIANN Dynamic Infrared-Rain Rate (PDIR-Now): A Near-Real-Time, Quasi-Global Satellite Precipitation Dataset.

S. Sorooshian, D. Bolvin, K. Hsu, 2020, Journal of hydrometeorology.

Unconfined Strength of Nano Reactive Silica Sand Powder Concrete

M. Sadeghi, H. Kabir, 2017 .

Application of remote sensing precipitation data and the CONNECT algorithm to investigate spatiotemporal variations of heavy precipitation: Case study of major floods across Iran (Spring 2019)

S. Sorooshian, M. Sadeghi, P. Nguyen, 2021 .

AML M1 presenting with recurrent acute large arterial vessel thromboembolism.

M. Sadeghi, B. Emmerich, F. Oduncu, 2007, Leukemia research.

Application of machine learning algorithms in hydrology

Hamid Reza Pourghasemi, Mojtaba Sadeghi, Mojtaba Naghdyzadegan Jahromi, 2022, Computers in Earth and Environmental Sciences.

PERSIANN-CCS-CDR, a 3-hourly 0.04° global precipitation climate data record for heavy precipitation studies

S. Sorooshian, K. Hsu, M. Sadeghi, 2021, Scientific data.

The study of the Rate of Users Satisfaction with the Book of “Relative Value of Health Services” in 2015

M. Sadeghi, Mostafa Damroodi, Amir Sinaei Rad, 2016 .

Improving near real-time precipitation estimation using a U-Net convolutional neural network and geographical information

Soroosh Sorooshian, Mojtaba Sadeghi, Phu Nguyen, 2020, Environ. Model. Softw..

Evaluation of PERSIANN-CDR Constructed Using GPCP V2.2 and V2.3 and A Comparison with TRMM 3B42 V7 and CPC Unified Gauge-Based Analysis in Global Scale

Soroosh Sorooshian, Mojtaba Sadeghi, Kuolin Hsu, 2019, Remote. Sens..

Spatiotemporal Variations of Precipitation over Iran Using the High-Resolution and Nearly Four Decades Satellite-Based PERSIANN-CDR Dataset

Negin Hayatbini, Soroosh Sorooshian, Mojtaba Sadeghi, 2020, Remote. Sens..

Explaining the Challenges and Solutions for Implementing Smart Systems in the Health System

M. Sadeghi, N. Mehrabi, Mobin Mohammadi, 2021 .

Estimation of Spatial Distribution of PM10, Lead, and Radon Concentrations in Sepahanshahr, Iran Using Geographic Information System (GIS)

M. Sadeghi, Negar Jafari, Ali Abdolahnejad, 2018 .