Jingqian Qiao, Liang Zhang. X-Ray Object Detection Based on Pyramid Convolution and Strip Pooling[J]. Laser & Optoelectronics Progress, 2022, 59(4): 0410017
- Laser & Optoelectronics Progress
- Vol. 59, Issue 4, 0410017 (2022)
Fig. 1. Gauss heat map of central key points. (a) Example 1; (b) example 2; (c) example 3; (d) example 4
Fig. 2. CenterNet detection algorithm
Fig. 3. Structure of Hourglass-104
Fig. 4. Standard convolution and Pyramid convolution
Fig. 5. Pyramid convolution kernel structure and pyramid convolution residual block structure. (a) Shallow layer pyramid convolution;(b) shallow middle layer pyramid convolution; (c) middle layer pyramid convolution; (d) deep layer pyramid convolution; (e) pyramid convolution residual block
Fig. 6. Pyramid Hourglass-104 network structure
Fig. 7. Strip pooling module
Fig. 8. Strip pooling head. (a) Sharing scheme; (b) unshared scheme
Fig. 9. SIXray_OD dataset.(a) Example 1; (b) example 2; (c) example 3; (d) example 4
Fig. 10. Comparison of detection results. (a) CenterNet; (b) proposed algorithm
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Table 1. Statistics of SIXray_OD dataset
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Table 2. Comparative experimental results of different detection networks
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Table 3. Ablation experimental results of each improvement point
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Table 4. Pyramid convolution scheme
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Table 5. Comparison results of different pyramid convolution schemes
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Table 6. Experimental results of pyramid convolution using position comparison
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Table 7. Experimental results of strip pooling using position comparison
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