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Study on the influence of variable stride scale change on image recognition in CNN

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Abstract

After the research based on the progressing image classification recognition method of CNN, the paper aims at the problem that the size of feature size of output map of image with different complexity cannot be well solved by the constant value stride. We bring up the idea which based on the variable stride length for constraint parameters to selectively select the size of the stride. It is helpful to improve the efficiency of selective extraction and recognition of important features. Later studies have proved that the deficiency issue of complex image characteristic extraction due to the large stride size could be averted by adopting the variable stride length method based on constraint parameters. In the meantime, the method also avoids low recognition efficiency due to the image complexity is sparse and, also, the stride size of the image is too small. The theoretically calculated results are in good agreement with the experimental results.

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Acknowledgements

The Project was supported by the Natural Science Foundation of Liaoning Province (Grant No. 20170540131), Nature Science Foundation of Heilongjiang Province (Grant No.C201437), Natural Science Foundation of Heilongjiang Province (Grant No. QC2018082) and Basic Scientific Research Funds of Heilongjing Provincial Higher Education lnstitutions (Grant No. 2017-KYYWF-0140). And we wish to thank the anonymous reviewers who helped to improve the quality of the paper.

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Authors and Affiliations

  1. Software Technology Institute, Dalian Jiaotong University, Dalian, 116021, China

    Chen Guo

  2. College of Computer Science, Harbin Normal University, Harbin, 150025, China

    Yue-lan Liu

  3. School of Information and Business Management, Dalian Neusoft University of Information, Dalian, 116021, China

    Xuan Jiao

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  1. Chen Guo
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  2. Yue-lan Liu
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  3. Xuan Jiao
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Correspondence to Yue-lan Liu.

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Guo, C., Liu, Yl. & Jiao, X. Study on the influence of variable stride scale change on image recognition in CNN. Multimed Tools Appl 78, 30027–30037 (2019). https://doi.org/10.1007/s11042-018-6861-0

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  • DOI: https://doi.org/10.1007/s11042-018-6861-0

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