Mohammad Pashaei
Datos Biográficos
| ID | 9965058 |
|---|---|
| NOMBRE | Mohammad Pashaei |
| NOMBRES | Mohammad |
| APELLIDO | Pashaei |
| FIRMA | PASHAEI M |
| AFILIACIONES | Texas A&M University – Corpus Christi |
| ORCID | 0000-0002-1427-6265 |
| VERIFICADO | Sí |
| TOTAL DE OBRAS | 1 |
| TOTAL DE CITAS | 0 |
| TOTAL COMO AUTOR | 1 |
| TOTAL COMO EDITOR | 0 |
| PRIMER AÑO DE PUBLICACIÓN | 2020 |
| AÑO MÁS RECIENTE DE PUBLICACIÓN | 2020 |
| ÍNDICE H | 0 |
A Deep Learning Approach to Urban Street Functionality Prediction Based on Centrality Measures and Stacked Denoising Autoencoder
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
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)