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DSSEMFF: A Depthwise Separable Squeeze-and-excitation Based on Multi-feature Fusion for Image Classification

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Abstract

Image classification refers to the classification of the input image according to some algorithms. The general steps of image classification include image preprocessing, image feature extraction and image classification judgment. Convolutional neural network (CNN) imitates the visual perception mechanism of biology, solves the complicated engineering of traditional manual feature extraction, and realizes automatic feature extraction from data. However, CNN still has the disadvantages of low efficiency and incomplete feature extraction. In this paper, we propose a depthwise separable squeeze-and-excitation based on multi-feature fusion (DSSEMFF) for image classification. Through feature fusion of multiple models, the network can learn the input features with different levels of images, increase feature complementarity and improve feature extraction ability. By adding the attention module, the network can pay more attention to the targeted area and reduce irrelevant background interference information. Finally, we conduct experiments with other state-of-the-art classification methods, the accuracy is higher than 90% and the error rate is lower than 18% the results show that the effectiveness of the proposed method obtains the better effect.

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Acknowledgements

Key Scientific Research Project of Higher Education in Henan Province, Education Science and Technology (2021) No. 383. Project Number: 22B510016. Project name: Air quality monitoring system based on LoRa spread spectrum modulation technology.

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Authors and Affiliations

  1. College of Information Engineering, Zhengzhou University of Science and Technology, Zhengzhou, 450000, People’s Republic of China

    Junjun Liu

  2. Office of Academic Affairs, Zhengzhou University of Science and Technology, Zhengzhou, 450000, People’s Republic of China

    Jun Zhang

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  1. Junjun Liu
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  2. Jun Zhang
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Correspondence to Jun Zhang.

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Liu, J., Zhang, J. DSSEMFF: A Depthwise Separable Squeeze-and-excitation Based on Multi-feature Fusion for Image Classification. Sens Imaging 23, 16 (2022). https://doi.org/10.1007/s11220-022-00383-5

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  • DOI: https://doi.org/10.1007/s11220-022-00383-5

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