Sustainable Flood Risk Identification and Assessment Using Artificial Intelligence: A Literature Review and Case Scenario-Reference-Cited by-同舟云学术

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Sustainable Flood Risk Identification and Assessment Using Artificial Intelligence: A Literature Review and Case Scenario

Published:2024-05-14 Issue: Volume:17 Page:25-30
ISSN:
Container-title:2024 IEEE World Forum on Public Safety Technology (WFPST)
language:
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Author:

Ahmed Imran¹,Ahmad Misbah²,Chehri Abdellah³,Joen Gwanggil⁴

Affiliation:

1. Anglia Ruskin University,School of Comp.Inf. Science,Cambridge,UK

2. University of the West of Hartpury and University,Bristol, and Gloucester,UK

3. Royal Military College of Canada,Dept. Math. Comp. Science,Kingston,Canada

4. Incheon National University,Dep. of Elect. Com. Eng.,Incheon,Korea

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx8/10606965/10606975/10607007.pdf?arnumber=10607007

Reference36 articles.

1. Fine-Grained Land Segmentation for Climate Change Impact Assessment: Leveraging the DeepGlobe Dataset with Advanced AI-driven Geospatial Analysis Techniques;El Maachi;ECTI-CIT Transactions,2023

2. Vision of IoT, 5G and 6G Data Processing: Applications in Climate Change Mitigation

3. Convolutional neural network–based person tracking using overhead views

4. Global Environmental Governance, Technology and Politics

5. Efficient topview person detector using point based transformation and lookup table

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