On Optimizing Model Generality in AI-based Disaster Damage Assessment: A Subjective Logic-driven Crowd-AI Hybrid Learning Approach

Yang Zhang; Ruohan Zong; Lanyu Shang; Huimin Zeng; Zhenrui Yue; Na Wei; Dong Wang

On Optimizing Model Generality in AI-based Disaster Damage Assessment: A Subjective Logic-driven Crowd-AI Hybrid Learning Approach

Yang Zhang, Ruohan Zong, Lanyu Shang, Huimin Zeng, Zhenrui Yue, Na Wei, Dong Wang

Computer Science

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Original language	English
Title of host publication	Proceedings Of The Thirty-second International Joint Conference On Artificial Intelligence, Ijcai 2023
Editors	E Elkind
Pages	6317-6325
Number of pages	9
State	Published - 2023

Cite this

On Optimizing Model Generality in AI-based Disaster Damage Assessment: A Subjective Logic-driven Crowd-AI Hybrid Learning Approach. / Zhang, Yang; Zong, Ruohan; Shang, Lanyu et al.
Proceedings Of The Thirty-second International Joint Conference On Artificial Intelligence, Ijcai 2023. ed. / E Elkind. 2023. p. 6317-6325.

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

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On Optimizing Model Generality in AI-based Disaster Damage Assessment: A Subjective Logic-driven Crowd-AI Hybrid Learning Approach

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