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ETHNOS_APP

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Mohammad Pashaei

Dados Biográficos

ID9965058
NOMEMohammad Pashaei
PRENOMESMohammad
SOBRENOMEPashaei
ASSINATURAPASHAEI M
AFILIAÇÕESTexas A&M University – Corpus Christi
ORCID0000-0002-1427-6265
VERIFICADOSim
TOTAL DE OBRAS1
TOTAL DE CITAÇÕES0
TOTAL COMO AUTOR1
TOTAL COMO EDITOR0
PRIMEIRO ANO DE PUBLICAÇÃO2020
ANO MAIS RECENTE DE PUBLICAÇÃO2020
ÍNDICE H0
  • A Deep Learning Approach to Urban Street Functionality Prediction Based on Centrality Measures and Stacked Denoising Autoencoder

    Open Access•Fatemeh Noori, Hamid Kamangir et al.•ARTICLE•ISPRS International Journal of…•2020

    In urban planning and transportation management, the centrality characteristics of urban streets are vital measures to consider. Centrality can help in understanding the structural properties of dense traffic networks that affect both human life and activity in cities. Many cities classify urban streets to provide stakeholders with a group of street guidelines for possible new rehabilitation such as sidewalks, curbs, and setbacks. Transportation …

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  • A Deep Learning Approach to Urban Street Functionality Prediction Based on Centrality Measures and Stacked Denoising Autoencoder

    Open Access•Fatemeh Noori, Hamid Kamangir et al.•ARTICLE•ISPRS International Journal of…•2020

    In urban planning and transportation management, the centrality characteristics of urban streets are vital measures to consider. Centrality can help in understanding the structural properties of dense traffic networks that affect both human life and activity in cities. Many cities classify urban streets to provide stakeholders with a group of street guidelines for possible new rehabilitation such as sidewalks, curbs, and setbacks. Transportation …

Artificial Intelligence (1 obras) · Autoencoder (1 obras) · Automated Road and Building Extraction (1 obras) · Centrality (1 obras) · Computer Science (1 obras) · Deep learning (1 obras) · Engineering (1 obras) · Geography (1 obras) · Human Mobility and Location-Based Analysis (1 obras) · Mathematics (1 obras)

Ethnos_APP • Projeto Open Source • Licença MIT • Frontend v2.0.0 • Privacidade e Cookies • Documentação da API: api.ethnos.app/docs • Código da API: GitHub • DOI: 10.5281/zenodo.17049435 • Código do Frontend: GitHub • DOI: 10.5281/zenodo.17050053 • cruz.rio.br • Expectantes Misericordiae