Evaluation on a Method of Detecting Suspicious Objects with Transformer Model Using Passive and Active Imagers of W-band Radar

Erika Saito*, Wataru Kameyama, Toshio Sato, Yutaka Katsuyama, Takuro Sato

*Corresponding author for this work

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

Abstract

We are studying a method to improve the accuracy of detecting suspicious objects carried by walking persons using both passive and active imager images taken by the W-band radar system. In this paper, we propose a transformer model based on our previously proposed CNN-based model. According to the experiment, the proposed transformer model achieves better accuracy on suspicious object detection than our previously proposed CNN-based model.

Original languageEnglish
Title of host publicationGCCE 2023 - 2023 IEEE 12th Global Conference on Consumer Electronics
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages736-737
Number of pages2
ISBN (Electronic)9798350340181
DOIs
Publication statusPublished - 2023
Event12th IEEE Global Conference on Consumer Electronics, GCCE 2023 - Nara, Japan
Duration: 2023 Oct 102023 Oct 13

Publication series

NameGCCE 2023 - 2023 IEEE 12th Global Conference on Consumer Electronics

Conference

Conference12th IEEE Global Conference on Consumer Electronics, GCCE 2023
Country/TerritoryJapan
CityNara
Period23/10/1023/10/13

Keywords

  • Active Imager
  • CNN
  • Passive Imager
  • Suspicious Object Detection
  • Transformer
  • W-band Radar

ASJC Scopus subject areas

  • Artificial Intelligence
  • Energy Engineering and Power Technology
  • Electrical and Electronic Engineering
  • Safety, Risk, Reliability and Quality
  • Instrumentation
  • Atomic and Molecular Physics, and Optics

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