Laser & Optoelectronics Progress, Volume. 56, Issue 4, 041502(2019)
Mask R-CNN Object Detection Method Based on Improved Feature Pyramid
The Mask R-CNN (mask region-based convolutional neural network) object detection method is proposed based on the improved feature pyramid. The experimental results show that compared with the Mask R-CNN detection structure, the mean average precision (mAP) under different Intersection-over-Union (IoU) thresholds increases by 2.4% and 3.8% in the detection of object edge and bounding box, respectively. In particular, the detection accuracy of medium size objects is greatly improved by 7.7% and 8.5%, respectively, which indicates strong robustness.
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Zhijun Ren, Suzhen Lin, Dawei Li, Lifang Wang, Jianhong Zuo. Mask R-CNN Object Detection Method Based on Improved Feature Pyramid[J]. Laser & Optoelectronics Progress, 2019, 56(4): 041502
Category: Machine Vision
Received: Aug. 27, 2018
Accepted: Sep. 4, 2018
Published Online: Jul. 31, 2019
The Author Email: Lin Suzhen (lsz@nuc.edu.cn)