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RETRACTED ARTICLE: Complex image recognition algorithm based on immune random forest model

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This article was retracted on 20 December 2022

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Abstract

With the continuous advancement of science and technology, the social network based on the Internet has gradually penetrated into people’s daily lives. The image data shared on social media using platforms such as mobile phones has exploded, and hundreds of millions of dollars are generated every day with picture information. In the past, the traditional ways of expressing textual information that people are familiar with have begun to be gradually replaced by image information that is not subject to regional culture such as language and script. In modern warfare, with the continuous development and equipment of highly sophisticated weapons and equipment, the amount of information that the entire combat system needs to process will also increase. In particular, the air defense system needs to quickly and accurately identify the aircraft targets that are coming. It mainly uses computer to extract the feature information of the acquired image and converts the content in the image into a feature expression that can be processed by the computer. After the appropriate classification algorithm, the image is the target object is classified by category. In this paper, we propose a complex image recognition algorithm based on immune random forest model. The experimental results show that the proposed algorithm has high recognition efficiency and higher robustness.

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Acknowledgement

This research was supported by the National Natural Science Foundation of China (Nos. 61872242, 61502220, 61775139, 61572326); the National Key Research and Development Program of China (No. 2018YFC0810204), Shanghai Science and Technology Innovation Action Plan Project (16111107502, 17511107203) and the program for tackling key problems in Henan science and technology (No.172102310636) for funding.

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Authors and Affiliations

  1. Zhengzhou University of Aeronautics, Zhengzhou, China

    Xiaoyu Zhang

  2. University of Shanghai for Science and Technology, Shanghai, China

    Wei Huang, Xiao Lin, Linhua Jiang & Chunxue Wu

  3. Shanghai Normal University, Shanghai, China

    Xiao Lin

  4. Indiana University, Bloomington, USA

    Yan Wu

Authors
  1. Xiaoyu Zhang
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  2. Wei Huang
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  3. Xiao Lin
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  4. Linhua Jiang
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  5. Yan Wu
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  6. Chunxue Wu
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Correspondence to Xiao Lin.

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Communicated by V. Loia.

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This article has been retracted. Please see the retraction notice for more detail: https://doi.org/10.1007/s00500-022-07753-x"

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Zhang, X., Huang, W., Lin, X. et al. RETRACTED ARTICLE: Complex image recognition algorithm based on immune random forest model. Soft Comput 24, 12643–12657 (2020). https://doi.org/10.1007/s00500-020-04706-0

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