Author Affiliations
1School of Resource Engineering, Xi'an University of Architecture and Technology, Xi'an , Shaanxi 710055, China2Xi'an Key Laboratory of Smart Industry Perception Computing and Decision Making, Xi'an , Shaanxi 710055, Chinashow less
Fig. 1. Structure of VGG network
Fig. 2. Structure of deformable convolution module
Fig. 3. Schematic of convolution sampling points. (a) Standard convolution; (b) deformable convolution
Fig. 4. Expansion results of convolution kernel of 3×3 size under different cavity rates. (a) l=1; (b) l=2; (c) l=3
Fig. 5. Framework structure of proposed network
Fig. 6. Images before and after bilateral filtering. (a) Original image of ore; (b) image filtered by 3×3 filtering window
Fig. 7. Relationship among loss, accuracy, and iterations of improved HED network model. (a) Loss; (b) accuracy
Fig. 8. Segmentation results of different network models. (a) Original images; (b) Canny operator; (c) original HED network; (d) improved HED network
Parameter | Value |
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Number of calculations | 300 | Iterations | 100 | Number of images per iteration | 4 | Number of training samples | 1000 |
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Table 1. Training parameters of model
Image | Accuracy | Recall | Precision |
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Canny | HED | Improved HED | Canny | HED | Improved HED | Canny | HED | Improved HED |
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1 | 0.7283 | 0.8172 | 0.9183 | 0.8162 | 0.8438 | 0.8275 | 0.8754 | 0.9219 | 0.9428 | 2 | 0.7882 | 0.8635 | 0.9117 | 0.8225 | 0.8035 | 0.8173 | 0.8829 | 0.9178 | 0.9537 | 3 | 0.7937 | 0.8879 | 0.9225 | 0.8156 | 0.8167 | 0.8158 | 0.8478 | 0.9378 | 0.9389 | 4 | 0.7014 | 0.8918 | 0.9308 | 0.8068 | 0.8124 | 0.8067 | 0.8513 | 0.9247 | 0.9409 | 5 | 0.7691 | 0.8815 | 0.9126 | 0.7995 | 0.8037 | 0.8117 | 0.8218 | 0.9345 | 0.9128 | 6 | 0.7437 | 0.8857 | 0.9215 | 0.8093 | 0.7969 | 0.8027 | 0.8145 | 0.9362 | 0.9390 | 7 | 0.7659 | 0.8972 | 0.9118 | 0.8109 | 0.8089 | 0.8164 | 0.8047 | 0.9419 | 0.9268 | 8 | 0.7573 | 0.8027 | 0.9169 | 0.8038 | 0.8129 | 0.8058 | 0.8439 | 0.9370 | 0.9503 | 9 | 0.7654 | 0.8896 | 0.9027 | 0.7995 | 0.8097 | 0.8187 | 0.8057 | 0.9105 | 0.9218 | 10 | 0.7715 | 0.8889 | 0.9047 | 0.8092 | 0.8126 | 0.8213 | 0.8120 | 0.9279 | 0.9348 | Average | 0.7585 | 0.8706 | 0.9154 | 0.8093 | 0.8121 | 0.8144 | 0.8360 | 0.9290 | 0.9362 |
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Table 2. Performance indicators of different networks
Model | MIOU /% | Time /ms |
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Canny | 72.62 | 128 | HED | 76.49 | 98 | Improved HED | 77.23 | 81 |
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Table 3. Time comparison results of different networks
Experiment | DCN | DC | AP /% |
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1 | × | × | 85.47 | 2 | √ | × | 90.23 | 3 | √ | √ | 92.37 |
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Table 4. Ablation experiment results of different network models