AI-Based W-Band Suspicious Object Detection System for Moving Persons Using GAN: Solutions, Performance Evaluation and Standardization Activities

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

Abstract

With the intensification of conflicts in different regions, the W-band suspicious object detection system is an essential security means to prevent terrorist attacks and is widely used in many crucial places such as airports. Because artificial intelligence can perform highly reliable and accurate services in the field of image recognition, it is used in suspicious object detection systems to increase the recognition rate for suspicious objects. However, it is challenging to establish a complete suspicious object database, and obtaining sufficient millimeter-wave images of suspicious objects from experiments for AI training is not realistic. To address this issue, this paper verifies the feasibility to generate a large number of millimeter-wave images for AI training by generative adversarial networks. Moreover, we also evaluate the factors that affect the AI recognition rate when the original images used for CNN training are insufficient and how to increase the service quality of AI-based W-band suspicious object detection systems for moving persons. In parallel, all the international standardization organizations have been collectively advancing the novel technologies of AI. We update the reader with information about AI research and standardization related activities in this paper.

Original languageEnglish
Title of host publication2020 ITU Kaleidoscope
Subtitle of host publicationIndustry-Driven Digital Transformation, ITU K 2020
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9789261313913
DOIs
Publication statusPublished - 2020 Dec 7
Event12th ITU Kaleidoscope: Industry-Driven Digital Transformation, ITU K 2020 - Virtual, Ha Noi, Viet Nam
Duration: 2020 Dec 72020 Dec 11

Publication series

Name2020 ITU Kaleidoscope: Industry-Driven Digital Transformation, ITU K 2020

Conference

Conference12th ITU Kaleidoscope: Industry-Driven Digital Transformation, ITU K 2020
Country/TerritoryViet Nam
CityVirtual, Ha Noi
Period20/12/720/12/11

Keywords

  • Artificial intelligence
  • generative adversarial network
  • millimeter-wave imaging
  • suspicious object detection system

ASJC Scopus subject areas

  • Management of Technology and Innovation
  • Artificial Intelligence
  • Computer Networks and Communications
  • Information Systems
  • Information Systems and Management
  • Industrial and Manufacturing Engineering

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