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松弛图嵌入的判别宽度学习系统以及在视觉识别中的应用

金军委 常少凯 耿彪 李艳婷 赵孟 王震 陈俊龙 李鹏

自动化学报2025,Vol.51Issue(6):1388-1402,15.
自动化学报2025,Vol.51Issue(6):1388-1402,15.DOI:10.16383/j.aas.c240734

松弛图嵌入的判别宽度学习系统以及在视觉识别中的应用

Relaxed-graph Embedding Discriminative Broad Learning System and Its Application in Visual Recognition

金军委 1常少凯 1耿彪 2李艳婷 3赵孟 1王震 4陈俊龙 5李鹏6

作者信息

  • 1. 河南工业大学人工智能与大数据学院 郑州 450001 中国
  • 2. 河南工业大学人工智能与大数据学院 郑州 450001 中国||新南威尔士大学计算机科学与工程学院 悉尼 NSW 2052 澳大利亚
  • 3. 郑州轻工业大学计算机科学与技术学院 郑州 450001 中国
  • 4. 西北工业大学网络空间安全学院 西安 710072 中国
  • 5. 华南理工大学计算机科学与工程学院 广州 510641 中国
  • 6. 河南工业大学复杂性科学研究院 郑州 450001 中国
  • 折叠

摘要

Abstract

The broad learning system,as a lightweight network,achieves a good balance between efficiency and ac-curacy.However,it primarily relies on strict binary labels for supervision and neglects local structural information during data transformation,limiting the model's performance.To address this issue,this paper proposes a relaxed-graph embedding discriminative broad learning system model and applies it to visual recognition,with the goal of enhancing model performance through the introduction of flexible labels and a relaxed-graph structure.The innova-tions of this paper are as follows:1)We innovatively use double transformation matrices to construct the relaxed-graph,separating the responsibilities of the transformation matrix.This reduces the burden on the transformation matrix and allows for the learning of more flexible transformation matrix,thereby mitigating the overfitting prob-lem;2)We introduce a flexible label strategy that increases the distance between different categories labels,address-ing the issue of strict binary labels,and thereby enhancing the model's discriminative ability;3)An iterative optim-ization algorithm based on the alternating direction method of multipliers is proposed to achieve efficient model op-timization.Extensive experiments on facial image datasets,object image datasets,scene image datasets and hand-written character image datasets demonstrate that the proposed model outperforms other advanced recognition al-gorithms.

关键词

宽度学习系统/松弛图/柔性标签/视觉识别

Key words

Broad learning system/relaxed-graph/flexible label/visual recognition

引用本文复制引用

金军委,常少凯,耿彪,李艳婷,赵孟,王震,陈俊龙,李鹏..松弛图嵌入的判别宽度学习系统以及在视觉识别中的应用[J].自动化学报,2025,51(6):1388-1402,15.

基金项目

国家自然科学基金(62106068,62106233,62073123,62375078,U1813203),河南省科技攻关项目(222102210058,232102210062,232102210007)资助Supported by National Natural Science Foundation of China(62106068,62106233,62073123,62375078,U1813203)and Sci-ence and Technology Research Project of Henan Province(222102210058,232102210062,232102210007) (62106068,62106233,62073123,62375078,U1813203)

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