Xunsheng Ji, Bin Teng. Detection of Abnormal Escalator Behavior Based on Deep Neural Network[J]. Laser & Optoelectronics Progress, 2020, 57(6): 061010
- Laser & Optoelectronics Progress
- Vol. 57, Issue 6, 061010 (2020)
Fig. 1. Network structure of Tiny YOLOv3
Fig. 2. Structure of standard convolution filters
Fig. 3. Structure of deep convolution filters
Fig. 4. Structure of pointwise convolution filters
Fig. 5. Network structure of improved model
Fig. 6. IOU of different number of priori boxes
Fig. 7. Tendency of loss function
Fig. 8. Detection results of Faster RCNN
Fig. 9. Detection results of SSD
Fig. 10. Detection results of YOLOv3
Fig. 11. Detection results of Tiny YOLOv3
Fig. 12. Detection results of our algorithm
Fig. 13. P-R curves of five algorithms
Fig. 14. Detection results of three algorithms for large targets. (a) YOLOv3; (b) Tiny YOLOv3; (c) proposed algorithm
Fig. 15. Detection results of three algorithms for small targets. (a) YOLOv3; (b) Tiny YOLOv3; (c) proposed algorithm
|
Table 1. 18-layer deep separable convolution structure
|
Table 2. Width and height of priori box corresponding to different k values
|
Table 3. Analysis of abnormal target detection performance for five different algorithms
Set citation alerts for the article
Please enter your email address
© Copyright 2018-2021 | Chinese Laser Press. All Rights Reserved 沪ICP备15018463号-20