Guixiong LIU, Jian HUANG. Transfer learning techniques for semantic segmentation of machine vision inspection and identification based on label-reserved Softmax algorithms[J]. Optics and Precision Engineering, 2022, 30(1): 117
- Optics and Precision Engineering
- Vol. 30, Issue 1, 117 (2022)
Fig. 1. Fine-tuning transfer learning framework based on label-reserved improved Softmax algorithms
Fig. 2. Model of label-reserved improved Softmax algorithms
Fig. 3. Head architecture of label-reserved Mask R-CNN
Fig. 4. Comparison of different migration learning methods
Fig. 5. Semantic segmentation results of chassis assemblies
Fig. 6. Basic functions of MVAQ2 chassis standard parts assembly quality inspection and identification software
Fig. 7. MVAQ2 chassis standard parts assembly quality inspection and identification devices
Fig. 8. Chassis learning process of MVAQ2 devices
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Table 1. T train and L CE of pre-trained Mask R-CNN model fine-tuning transfer learning initial various weights W
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Table 2. Parameter comparison of label-reserved and general Softmax algorithms
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Table 3. Training time ofdifferent transfer learning methods
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