Image-based Hazard Classification
Image-Based Hazard Classification is a methodological framework within hazard classification that utilizes visual data as primary input to identify, categorize, and assess potential hazards through computational analysis of spatial, spectral, or temporal image features.
20
Publications
585
Citations
52
Authors
27
Institutions
Publications per year
2017–2026
14
Parents
20
1–5 of 20
52
1
h-index
1
h-index
1
h-index
1 publications · 14 citations
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1
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1–5 of 52
27
California Institute of Technology
Pasadena, United States
1 h-index
1 publications
18 citations
Xi’an Jiaotong-Liverpool University
Suzhou, China
1 h-index
1 publications
19 citations
Pusan National University
Busan, South Korea
1 h-index
3 publications
57 citations
China University of Mining and Technology
Xuzhou, China
1 h-index
5 publications
80 citations
NIHR Manchester Biomedical Research Centre
Manchester, United Kingdom
1 h-index
1 publications
27 citations

Southeast University
Nanjing, China
1 h-index
1 publications
64 citations
National Water Research Center
Cairo, Egypt
1 h-index
1 publications
10 citations
Karlsruhe Institute of Technology
Karlsruhe, Germany
1 h-index
3 publications
48 citations
1–8 of 27
1 publications · 55 citations
1
h-index
1 publications · 27 citations
1
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FGCS · 1 publications · 19 citations
1
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1 publications · 10 citations
1
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1 publications · 16 citations
1
h-index
1–5