[1] |
Li Mao.Instrument digital image recognition and application research[D].Guangzhou:Guangdong University of Technology,2006.(in Chinese)
|
[2] |
Chi Tie,Ma Bin,Han Zhong-hua,et al.Instrument digital image recognition and application[J].Electronic Engineering & Product World,2010,17(11):24-26.(in Chinese)
|
[3] |
Guo Shi-xiong.Study on the technology of digital recognition in medical instrument[D].Xi’an:Xi’an University of Architecture and Technology,2009.(in Chinese)
|
[4] |
Strathy N W,Suen C Y,Krzyzak A,et al.Segmentation of handwritten digits using contour features[C]∥Proc of International Conference on Document Analysis and Recognition,1993:577-580.
|
[5] |
Lu Z K, Chi Z R, Siu W C,et al.A background-thinning-based approach for separating and recognizing connected handwritten digit strings[J].Pattern Recognition,1999,32(6):921-933.
|
[6] |
Lu Da, Xie Ming-pei, Qian Yi-ping, et al.A segmentation method of topographic approach for merged character images based on skeletonization[J].Journal of Chinese Information Processing,1999,13(2):40-45.(in Chinese)
|
[7] |
Shen Xiao-yang.The computer automatic recognition character of numeral instrument dynamic displayed[D].Hangzhou:Zhejiang University of Technology,2005.(in Chinese)
|
[8] |
Cortes C, Vapnik V. Support-vector networks[J]. Machine learning, 1995, 20(3): 273-297.
|
[9] |
Krizhevsky A,Sutskever I,Hinton G E,et al.ImageNet classification with deep convolutional neural networks[C]∥Proc of International Conference on Neural Information Processing Systems,2012:1097-1105.
|
[10] |
Girshick R,Donahue J,Darrell T,et al.Rich feature hierarchies for accurate object detection and semantic segmentation[C]∥Proc of 2014 IEEE Conference on Computer Vision and Pattern Recognition,2014:580-587.
|
[11] |
Uijlings J R R,van de Sande K E A,Gevers T,et al.Selective search for object recognition[J]. International Journal of Computer Vision, 2013,104:154-171.
|
[12] |
He K M,Zhang X Y,Ren S Q,et al.Spatial pyramid pooling in deep convolutional networks for visual recognition[J].IEEE Transactions on Pattern Analysis & Machine Intelligence,2015,37(9):1904-1916.
|
[13] |
Girshick R.Fast R-CNN[C]∥Proc of International Confe- rence on Computer Vision,2015:1440-1448.
|
[14] |
Ren S, He K, Girshick R, et al. Faster R-CNN:Towards real-time object detection with region proposal networks[C]∥Proc of International Conference on Neural Information Processing Systems,2015:91-99.
|
[15] |
Long J,Shelhamer E,Darrell T,et al.Fully convolutional networks for semantic segmentation[C]∥Proc of 2015 IEEE Conference on Computer Vision and Pattern Recognition,2015:3431-3440.
|
[16] |
Wang Ji-lin,Wang Hui-fang,Guan Min-yuan,et al.An automatic identification for reading of substation pointer-type meters using faster R-CNN and U-Net[J].Power System Technology,2020,44(8):3097-3105.(in Chinese)
|
[17] |
Sermanet P,Eigen D,Zhang X,et al.OverFeat:Integrated recognition,localization and detection using convolutional networks[J].arXiv:1312.6229,2013.
|
[18] |
Redmon J, Divvala S K,Girshick R,et al.You only look once:Unified,real-time object detection[C]∥Proc of 2016 IEEE Conference on Computer Vision and Pattern Recognition,2016:779-788.
|
[19] |
Zhang Jun. Machine vision-based intelligent algorithm for meter reading and its applications[D].Chengdu:University of Electronic Science and Technology,2019.(in Chinese)
|
[20] |
Liu W,Anguelov D,Erhan D,et al.SSD:Single shot multibox detector[C]∥Proc of European Conference on Computer Vision,2016:21-37.
|
[21] |
Wang Ming-kai.Reseach on detection method of automobile dashboard based on computer vision[D].Harbin:Harbin Institute of Technology,2019.(in Chinese)
|
[22] |
Zhang Si-yu, Zhang Yi.Small target pedestrian detection based on multi-scale feature fusion[J].Computer Engineering & Science,2019,41(9):1627-1634.(in Chinese)
|
[23] |
Redmon J,Farhadi A.YOLO9000:Better,faster,stronger[C]∥Proc of 2017 IEEE Conference on Computer Vision and Pattern Recognition,2017:6517-6525.
|
[24] |
Redmon J, Farhadi A.YOLOv3:An incremental improvement[J].arXiv:1804.02767,2018.
|
[25] |
Xiong Wei, Xiong Zi-jie,Yang Di-chun,et al.Pedestrian re- identification based on deep feature fusion[J].Computer Engineering & Science,2020,42(2):358-364.(in Chinese)
|
[26] |
Howard A,Zhu M,Chen B,et al.MobileNets:Efficient convolutional neural networks for mobile vision applications[J].arXiv:1704.04861,2017.
|
[27] |
Sandler M,Howard A,Zhu M,et al.MobileNetV2:Inverted residuals and linear bottlenecks[C]∥Proc of 2018 IEEE Conference on Computer Vision and Pattern Recognition,2018:4510-4520.
|
[28] |
Zhang X Y,Zhou X Y,Lin M X,et al.ShuffleNet:An extremely efficient convolutional neural network for mobile devices[C]∥Proc of 2018 IEEE Conference on Computer Vision and Pattern Recognition,2018:6848-6856.
|
[29] |
Ma N N,Zhang X Y,Zheng H T,et al.ShuffleNet V2:Practical guidelines for efficient CNN architecture design[C]∥Proc of European Conference on Computer Vision,2018:122-138.
|
[30] |
Simonyan K, Zisserman A.Very deep convolutional networks for large-scale image recognition[J]. arXiv:1409.1556,2014.
|
[31] |
Everingham M, Eslami S M A,Gool L V,et al.The pascal visual object classes challenge:A retrospective[J].International Journal of Computer Vision,2015,111(1):98-136.
|
[32] |
Luo W J,Li Y J,Urtasun R,et al.Understanding the effec- tive receptive field in deep convolutional neural networks[C]∥Proc of International Conference on Neural Information Processing Systems,2016:4898-4906.
|
|
附中文参考文献:
|
[1] |
李貌.仪器仪表数字图像识别及其应用研究[D].广州:广东工业大学,2006.
|
[2] |
迟铁,马斌,韩忠华,等.仪器仪表数字图像的识别及其应用[J].电子产品世界,2010,17(11):24-26.
|
[3] |
郭世雄.医疗仪器中的数字识别技术研究[D].西安:西安建筑科技大学,2009.
|
[6] |
卢达,谢铭培,钱忆平,等.一种基于骨架法形态分析的粘连字符图象分切方法[J].中文信息学报,1999,13(2):40-45.
|
[7] |
申小阳.数字仪表动态显示字符的计算机自动识别[D].杭州:浙江工业大学,2005.
|
[16] |
万吉林,王慧芳,管敏渊,等.基于Faster R-CNN和U-Net的变电站指针式仪表读数自动识别方法[J].电网技术,2020,44(8):3097-3105.
|
[19] |
张珺.基于机器视觉的仪表读数智能识别算法研究及应用[D].成都:电子科技大学,2019.
|
[21] |
王明凯.基于计算机视觉的汽车仪表检测方法的研究[D].哈尔滨:哈尔滨工业大学,2019.
|
[22] |
张思宇,张轶.基于多尺度特征融合的小目标行人检测[J].计算机工程与科学,2019,41(9):1627-1634.
|
[25] |
熊炜,熊子婕,杨荻椿,等.基于深层特征融合的行人重识别方法[J].计算机工程与科学,2020,42(2):358-364.
|