Hossein Bagheri

Biographic Data

ID6772131
NAMEHossein Bagheri
GIVEN NAMESHossein
FAMILY NAMEBagheri
SIGNATUREBAGHERI H
AFFILIATIONSUniversity of Isfahan
ORCID0000-0002-9692-6339
VERIFIEDYes
TOTAL WORKS6
TOTAL CITATIONS0
AUTHOR COUNT6
EDITOR COUNT0
FIRST PUBLICATION YEAR2023
LATEST PUBLICATION YEAR2026
H-INDEX0

  • Psychometric characteristics of the Persian version of the State Self-Compassion Scale in patients with cardiovascular diseases

    Open AccessSaeed Ghasempour, Hossein Bagheri et al.ARTICLEActa Psychologica2026

    Assessing self-compassion as a beneficial psychological feature and a compassionate mindset can only be accomplished with a valid and reliable instrument that facilitates convenient utilization in experimental or therapeutic settings. The State Self-Compassion Scale (SSCS), although possessing the aforementioned characteristics, has not yet undergone psychometric testing in clinical communities. Thus, the current study was undertaken to culturall…

  • Explaining ecological drivers and management implications of forest biomass

    Open AccessSina Irannejad, Hossein BagheriARTICLETrees Forests and People2026

    Multi-source deep learning framework improves forest biomass estimation. • Integration of Climate-FVS data enhances accuracy in complex terrains. • Explainable AI reveals key ecological drivers of aboveground biomass. • SWIR and Red bands identified as the most influential spectral predictors. • Findings support carbon accounting and sustainable forest management. Accurate estimation of aboveground biomass (AGB) is essential for sustainable fores…

  • Optimizing urban critical green space development using machine learning

    Open AccessMohammad Ganjirad, Mahmoud Reza Delavar et al.ARTICLESustainable Cities and Society2025

  • Assessing wildfire susceptibility in Iran

    Open AccessEhsan Masoudian, Ali Mirzaei et al.ARTICLETrees Forests and People2025

    This study investigates the multifaceted factors influencing wildfire risk in Iran, focusing on the interplay between climatic conditions and human activities. Utilizing advanced remote sensing, geospatial information system (GIS) processing techniques such as cloud computing, and machine learning algorithms, this research analyzed the impact of climatic parameters, topographic features, and human-related factors on wildfire susceptibility assess…

  • Iranian EFL Teachers' Perception of Computer, Information, Multimedia Literacy, and Demographic Background

    Farzad Sabeki, Hossein Bagheri et al.ARTICLEJOURNAL OF LANGUAGE STUDIES2023

    The purpose of the current study was to explore computer, information and multimedia literacy of Iranian EFL teachers with regard to their demographic background. In order to collect the data, Computer, Information, and Multimedia Literacy Questionnaire for EFL Teachers was distributed to 70 male and female Iranian EFL teachers from Sistan-Baluchestan and Hormozgan provinces. Demographic information of the teachers was operationalized through age…

  • Enhancing Crop Classification Accuracy through Synthetic SAR-Optical Data Generation Using Deep Learning

    Open AccessAli Mirzaei, Hossein Bagheri et al.ARTICLEISPRS International Journal of…2023

    Crop classification using remote sensing data has emerged as a prominent research area in recent decades. Studies have demonstrated that fusing synthetic aperture radar (SAR) and optical images can significantly enhance the accuracy of classification. However, a major challenge in this field is the limited availability of training data, which adversely affects the performance of classifiers. In agricultural regions, the dominant crops typically c…