@inproceedings{1bcb45ed74a549bb8dacccffc5ba9243,
title = "A Crowd-driven Dynamic Neural Architecture Searching Approach to Quality-aware Streaming Disaster Damage Assessment",
abstract = "Streaming disaster damage assessment (DDA) aims to automatically assess the damage severity of affected areas in a disaster event on the fly by leveraging the streaming imagery data about the disaster on social media. In this paper, we focus on a dynamic optimal neural architecture searching (NAS) problem in streaming DDA applications. Our goal is to dynamically determine the optimal neural network architecture that accurately estimates the damage severity for each newly-arrived image in the stream by leveraging human intelligence from the crowdsourcing systems. Our work is motivated by the observations that the neural network architectures in current DDA solutions are mainly designed by AI experts, which often leads to non-negligible costs and errors given the dynamic nature of the streaming DDA applications and the lack of real-time annotations of the massive social media data inputs. In this paper, we develop CD-NAS, a crowd-driven dynamic NAS framework that is inspired by novel techniques from AI, crowdsourcing, and estimation theory to address the dynamic optimal NAS problem. The evaluation results from a real-world streaming DDA application show that CD-NAS consistently outperforms the state-of-the-art AI and NAS baselines by achieving the highest disaster damage assessment accuracy.",
keywords = "Crowdsourcing, Social networking (online), Neural networks, Transportation, Quality of service, Estimation theory, Streaming media",
author = "Yang Zhang and Ruohan Zong and Ziyi Kou and Lanyu Shang and Dong Wang",
note = "Funding Information: This research is supported in part by the National Science Foundation under Grant No. IIS-2008228, CNS-1845639, CNS-1831669, Army Research Office under Grant W911NF-17-1-0409. The views and conclusions contained in this document are those of the authors and should not be interpreted as representing the official policies, either expressed or implied, of the Army Research Office or the U.S. Government. The U.S. Government is authorized to reproduce and distribute reprints for Government purposes notwithstanding any copyright notation here on. Publisher Copyright: {\textcopyright} 2021 IEEE.; 29th IEEE/ACM International Symposium on Quality of Service, IWQOS 2021 ; Conference date: 25-06-2021 Through 28-06-2021",
year = "2021",
month = jun,
day = "25",
doi = "10.1109/IWQOS52092.2021.9521346",
language = "English (US)",
isbn = "978-1-6654-3054-8",
series = "2021 IEEE/ACM 29th International Symposium on Quality of Service, IWQOS 2021",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "1--6",
booktitle = "2021 IEEE/ACM 29th International Symposium on Quality of Service, IWQOS 2021",
address = "United States",
}