作者
Keping Yu, Xin Qi, Toshio Sato, Zheng Wen, Yutaka Katsuyama, Kiyohito Tokuda, Wataru Kameyama, Takuro Sato
发表日期
2020/4/29
期刊
IEEE Access
卷号
8
页码范围
81378-81393
出版商
IEEE
简介
The threat of terrorism has spread all over the world, and the situation has become grave. Suspicious object detection in the Internet of Things (IoT) is an effective way to respond to global terrorist attacks. The traditional solution requires performing security checks one by one at the entrance of each gate, resulting in bottlenecks and crowding. In the IoT paradigm, it is necessary to be able to perform suspicious object detection on moving people. Artificial intelligence (AI) and millimeter-wave imaging are advanced technologies in the global security field. However, suspicious object detection for moving persons in the IoT, which requires the integration of many different imaging technologies, is still a challenge in both academia and industry. Furthermore, increasing the recognition rate of suspicious objects and controlling network congestion are two main issues for such a suspicious object detection system. In this …
引用总数
2020202120222023202469252