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基于改进特征金字塔的Mask R-CNN目标检测方法

Mask R-CNN Object Detection Method Based on Improved Feature Pyramid

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摘要

提出了一种基于改进特征金字塔的Mask R-CNN目标检测方法。实验结果表明,在目标边缘和包围盒两项检测中,相比于Mask R-CNN检测框架,所提方法在不同的交并比阈值下的平均准确率分别提高了约2.4%和3.8%。尤其?#26434;?#20013;等尺寸目标的检测准确率有较大的提高,分别为7.7%和8.5%,具有较强的稳健性。

Abstract

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.

Newport宣传-MKS新实验室计划
补充资料

中图分类号:TP391

DOI:10.3788/lop56.041502

所属?#25913;浚?a href='../Journals/JColumnList?cid=1408' title='查看该期刊此?#25913;?#19979;其他论文' class='TagKey' target='_blank'>机器视觉

基金项目:山西省应用基础研究项目(201701D121062)

收稿日期:2018-08-27

修改稿日期:2018-08-30

网络出版日期:2018-09-04

作者单位    点击查看

任之俊:中北大学大数据学院, 山西 太原 030051
蔺素珍:中北大学大数据学院, 山西 太原 030051
李大威:中北大学大数据学院, 山西 太原 030051
王丽芳:中北大学大数据学院, 山西 太原 030051
左健宏:中北大学大数据学院, 山西 太原 030051

联系人作者:蔺素珍([email protected])

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引用该论文

Ren Zhijun,Lin Suzhen,Li Dawei,Wang Lifang,Zuo Jianhong. Mask R-CNN Object Detection Method Based on Improved Feature Pyramid[J]. Laser & Optoelectronics Progress, 2019, 56(4): 041502

任之俊,蔺素珍,李大威,王丽芳,左健宏. 基于改进特征金字塔的Mask R-CNN目标检测方法[J]. 激光与光电子学进展, 2019, 56(4): 041502

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