| Presentation | 2023-01-11 Prohibited Items Detection in X-ray Security Inspection by Using a Deep Learning Method Qingqi Zhang, Ren Wu, Mitsuru Nakata, Qi-Wei Ge, |
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| PDF Download Page |  PDF download Page Link |
| Abstract(in Japanese) | (See Japanese page) |
| Abstract(in English) | Security screening machines using X-ray scanners are usually used to find out whether there are prohibited items in packages at airports, key venues and so on. The images after X-ray irradiation are characterized by monotone color and missing surface texture. These characteristics can make it more difficult to detect prohibited items in X-ray security inspection images. In this paper, we propose to use cascade network in deep learning to identifying prohibited items from X-ray security inspection images. To improve the detection accuracy of cascade network in prohibited items detection task as much as possible, we propose Re-BiFPN feature fusion method. Re-BiFPN structure is constructed by merging BiFPN layers into the bottom-up backbone layer through recursive connectivity to achieve more efficient cross-scale connectivity and weighted feature fusion. Experiments show that our proposed algorithm can successfully identify ten kinds of prohibited items such as Knife, Scissors, etc., and the algorithm achieves 83.4% of mAP. |
| Keyword(in Japanese) | (See Japanese page) |
| Keyword(in English) | X-ray security inspection / Prohibited items detection / Multi-scale feature fusion / Target detection |
| Paper # | MSS2022-52,SS2022-37 |
| Date of Issue | 2023-01-03 (MSS, SS) |
| Conference Information | |
| Committee | MSS / SS |
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| Conference Date | 2023/1/10(2days) |
| Place (in Japanese) | (See Japanese page) |
| Place (in English) | |
| Topics (in Japanese) | (See Japanese page) |
| Topics (in English) | |
| Chair | Atsuo Ozaki(Osaka Inst. of Tech.) / Kozo Okano(Shinshu Univ.) |
| Vice Chair | Shingo Yamaguchi(Yamaguchi Univ.) / Yoshiki Higo(Osaka Univ.) |
| Secretary | Shingo Yamaguchi(Hokkaido Univ.) / Yoshiki Higo(NEC) |
| Assistant | Masato Shirai(Shimane Univ.) / Shinsuke Matsumoto(Osaka Univ.) |
| Paper Information | |
| Registration To | Technical Committee on Mathematical Systems Science and its Applications / Technical Committee on Software Science |
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| Language | ENG-JTITLE |
| Title (in Japanese) | (See Japanese page) |
| Sub Title (in Japanese) | (See Japanese page) |
| Title (in English) | Prohibited Items Detection in X-ray Security Inspection by Using a Deep Learning Method |
| Sub Title (in English) | |
| Keyword(1) | X-ray security inspection |
| Keyword(2) | Prohibited items detection |
| Keyword(3) | Multi-scale feature fusion |
| Keyword(4) | Target detection |
| 1st Author's Name | Qingqi Zhang |
| 1st Author's Affiliation | Yamaguchi University(Yamaguchi Univ.) |
| 2nd Author's Name | Ren Wu |
| 2nd Author's Affiliation | Yamaguchi Junior College(Yamaguchi Junior College) |
| 3rd Author's Name | Mitsuru Nakata |
| 3rd Author's Affiliation | Yamaguchi University(Yamaguchi Univ.) |
| 4th Author's Name | Qi-Wei Ge |
| 4th Author's Affiliation | Yamaguchi University(Yamaguchi Univ.) |
| Date | 2023-01-11 |
| Paper # | MSS2022-52,SS2022-37 |
| Volume (vol) | vol.122 |
| Number (no) | MSS-329,SS-330 |
| Page | pp.pp.42-47(MSS), pp.42-47(SS), |
| #Pages | 6 |
| Date of Issue | 2023-01-03 (MSS, SS) |