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Classification algorithm for liquid dangerous goods based on WT-AE and Attention-GRU network

Published: 26 October 2023 Publication History

Abstract

To address the problem of low classification accuracy of liquid dangerous goods in daily security screening technology, we propose a two-layer feature extraction classification algorithm based on Ultra-Wideband centimeter wave detection, which is composed of shallow Wavelet Transform-Autoencoder (WT-AE) and deep Attention-Gated Recurrent Unit (Attention-GRU) network. In order to abstract the best description feature, the shallow autoencoder adds a classification constraint. In the classification stage, the deep algorithm Attention-GRU algorithm can further abstract the sequence composed of shallow features into deep features to improve the accuracy of classification. The experimental results show that the WT-AE algorithm with shallow constraint is more suitable for feature extraction of UWB centimeter-wave signals in this experimental scene than PCA and ICA feature extraction algorithms. Compared with KNN, Linear kernel SVM, Gaussian kernel SVM and decision tree algorithms for sequence processing, Attention-GRU has better processing effect and higher accuracy of classification. By comparing the test accuracy of other algorithms, the double-layer feature classification algorithm performs better in this experimental scene. The final test accuracy can reach 95.8%.

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          ICDIP '23: Proceedings of the 15th International Conference on Digital Image Processing
          May 2023
          711 pages
          ISBN:9798400708237
          DOI:10.1145/3604078
          Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than the author(s) must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected].

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          Association for Computing Machinery

          New York, NY, United States

          Publication History

          Published: 26 October 2023

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