Laser & Optoelectronics Progress, Volume. 57, Issue 20, 201021(2020)
Fire Detection Method Based on Localization Confidence and Region-Based Fully Convolutional Network
Fig. 1. Detection diagram of R-FCN
Fig. 2. Separable convolution
Fig. 3. Incomplete information marked by anchors
Fig. 4. Change of translation and scaling
Fig. 5. Comparison of iterations accuracy changes[11]. (a)FPN iterations accuracy changes; (b)R-CNN iterations accuracy changes
Fig. 6. Comparison of pooling. (a) ROI pooling; (b) precise ROI pooling
Fig. 7. Non-maximum suppression
Fig. 8. Lack of localization confidence of NMS
Fig. 9. Prediction of IOU
Fig. 10. Flow chart of LOF-FCN
Fig. 11. Comparison of fire missed detection rate
Fig. 12. Comparison of fire detection accuracy
Fig. 13. Experimental video. (a) Video 1; (b) video 2; (c) video 3; (d) video 4; (e) video 5; (f) video 6
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Hong Zhang, Yunyang Yan, Yian Liu, Shangbing Gao. Fire Detection Method Based on Localization Confidence and Region-Based Fully Convolutional Network[J]. Laser & Optoelectronics Progress, 2020, 57(20): 201021
Category: Image Processing
Received: Feb. 12, 2020
Accepted: Mar. 12, 2020
Published Online: Oct. 13, 2020
The Author Email: Yan Yunyang (yunyang@hyit.edu.cn)