Abstract
In this paper, we focus on the detection of prohibited items with small size, and establish an automatic detection model based on feature fusion single shot multibox detector (FSSD) architecture. Two modifications are carried out to improve the detection accuracy. Firstly, the semantic enrichment module (SEM) with dilated convolution is applied to extract the low level feature with strong semantic information. Secondly, a residual module (Res) with residual blocks is added in the multibox detection architecture in order to extract more adequate features for target detection. The simulation results have demonstrated a better performance of the proposed detection model for prohibited items with small size compared with the state-of-the-arts.
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This work has been supported by the National Natural Science Foundation of China (No.61806208), the Fundamental Research Funds for the Central Universities (No.3122018S008), and the Tianjin Education Committee Research Project (No.2018KJ246).
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Zhang, Yt., Zhang, Hg., Zhao, Tf. et al. Automatic detection of prohibited items with small size in X-ray images. Optoelectron. Lett. 16, 313–317 (2020). https://doi.org/10.1007/s11801-020-9118-x
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DOI: https://doi.org/10.1007/s11801-020-9118-x