A Crowd-driven Dynamic Neural Architecture Searching Approach to Quality-aware Streaming Disaster Damage Assessment

Yang Zhang, Ruohan Zong, Ziyi Kou, Lanyu Shang, Dong Wang

Research output: Chapter in Book/Report/Conference proceedingConference contribution

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.

Original languageEnglish (US)
Title of host publication2021 IEEE/ACM 29th International Symposium on Quality of Service, IWQOS 2021
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages1-6
Number of pages6
ISBN (Electronic)9781665414944
ISBN (Print)978-1-6654-3054-8
DOIs
StatePublished - Jun 25 2021
Externally publishedYes
Event29th IEEE/ACM International Symposium on Quality of Service, IWQOS 2021 - Virtual, Tokyo, Japan
Duration: Jun 25 2021Jun 28 2021

Publication series

Name2021 IEEE/ACM 29th International Symposium on Quality of Service, IWQOS 2021

Conference

Conference29th IEEE/ACM International Symposium on Quality of Service, IWQOS 2021
Country/TerritoryJapan
CityVirtual, Tokyo
Period6/25/216/28/21

Keywords

  • Crowdsourcing
  • Social networking (online)
  • Neural networks
  • Transportation
  • Quality of service
  • Estimation theory
  • Streaming media

ASJC Scopus subject areas

  • Computer Networks and Communications
  • Information Systems and Management
  • Safety, Risk, Reliability and Quality

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