Tianhong Zhao

Orcid: 0000-0002-9290-2049

According to our database1, Tianhong Zhao authored at least 11 papers between 2019 and 2024.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

Legend:

Book 
In proceedings 
Article 
PhD thesis 
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Links

On csauthors.net:

Bibliography

2024
Deep online recommendations for connected E-taxis by coupling trajectory mining and reinforcement learning.
Int. J. Geogr. Inf. Sci., February, 2024

2023
Incorporating multimodal context information into traffic speed forecasting through graph deep learning.
Int. J. Geogr. Inf. Sci., September, 2023

Sensitivity of measuring the urban form and greenery using street-level imagery: A comparative study of approaches and visual perspectives.
Int. J. Appl. Earth Obs. Geoinformation, August, 2023

Sensing urban soundscapes from street view imagery.
Comput. Environ. Urban Syst., 2023

Developing a multiview spatiotemporal model based on deep graph neural networks to predict the travel demand by bus.
Int. J. Geogr. Inf. Sci., 2023

2022
Coupling graph deep learning and spatial-temporal influence of built environment for short-term bus travel demand prediction.
Comput. Environ. Urban Syst., 2022

Optimizing Living Material Delivery During the COVID-19 Outbreak.
IEEE Trans. Intell. Transp. Syst., 2022

Correction: Yang et al. Detecting Spatiotemporal Features and Rationalities of Urban Expansions within the Guangdong-Hong Kong-Macau Greater Bay Area of China from 1987 to 2017 Using Time-Series Landsat Images and Socioeconomic Data. Remote Sens. 2019, 11, 2215.
Remote. Sens., 2022

2021
Collaboratively inspect large-area sewer pipe networks using pipe robotic capsules.
Proceedings of the SIGSPATIAL '21: 29th International Conference on Advances in Geographic Information Systems, 2021

2020
OCD: Online Crowdsourced Delivery for On-Demand Food.
IEEE Internet Things J., 2020

2019
Detecting Spatiotemporal Features and Rationalities of Urban Expansions within the Guangdong-Hong Kong-Macau Greater Bay Area of China from 1987 to 2017 Using Time-Series Landsat Images and Socioeconomic Data.
Remote. Sens., 2019


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