• Optics and Precision Engineering
  • Vol. 31, Issue 13, 2000 (2023)
Rui WANG1,*, Siyang FAN1, Jingwen XU1, and Zhiqing WEN2
Author Affiliations
  • 1Laboratory of Precision Opto-mechatronics Technology, Ministry of Education, Institute of Instrumentation Science and Opto-electronics Engineering, Beihang University, Beijing009, China
  • 2Engineering Research Center for Intelligent Robotics, Ji Hua Laboratory, Foshan5800, China
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    DOI: 10.37188/OPE.20233113.2000 Cite this Article
    Rui WANG, Siyang FAN, Jingwen XU, Zhiqing WEN. Semi-supervised instance object detection method based on SVD co-training[J]. Optics and Precision Engineering, 2023, 31(13): 2000 Copy Citation Text show less
    Flow chart of training SVD-RCNN
    Fig. 1. Flow chart of training SVD-RCNN
    Framework of key sample selection
    Fig. 2. Framework of key sample selection
    Comparison of Gram matrix before and after convergence, decomposition and finetuning
    Fig. 3. Comparison of Gram matrix before and after convergence, decomposition and finetuning
    Iteration accuracy of SVD-RCNN with different δacc
    Fig. 4. Iteration accuracy of SVD-RCNN with different δacc
    Detection accuracy of pre-training SVD-RCNN on GMU dataset
    Fig. 5. Detection accuracy of pre-training SVD-RCNN on GMU dataset
    Detection result on GMU, AVD and BHID datasets
    Fig. 6. Detection result on GMU, AVD and BHID datasets
    数据集关键样本数量收敛-分解-微调自适应的自标注mAP/%
    GMU19972.1
    19977.6
    19975.8
    19979.3
    Table 1. Results of ablation experiment
    数据集关键样本数量方 法mAP/%
    GMU199半监督SVD-RCNN79.3
    3 851全监督Faster RCNN81.3
    AVD255半监督SVD-RCNN75.6
    5 083全监督Faster RCNN78.5
    BHID55半监督SVD-RCNN76.1
    1 110全监督Faster RCNN78.4
    Table 2. Comparison of detection accuracy of training methods on different datasets

    数据集

    (标注样本数量)

    基础网络方 法mAP/%

    GMU

    (199)

    Faster RCNNUnbiased Teacher776.5
    Soft Teacher1978.3
    本文算法79.3
    Table 3. Comparison of semi-supervised methods on GMU
    Rui WANG, Siyang FAN, Jingwen XU, Zhiqing WEN. Semi-supervised instance object detection method based on SVD co-training[J]. Optics and Precision Engineering, 2023, 31(13): 2000
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