Journal of Shandong University(Engineering Science) ›› 2019, Vol. 49 ›› Issue (4): 1-7.doi: 10.6040/j.issn.1672-3961.0.2018.275
• Machine Learning & Data Mining • Next Articles
Yanghao ZHOU(),Yifan LIU,Li LI
CLC Number:
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陶冰洁, 韩佳乐, 李恩. 一种实用的指针式仪表读数识别方法[J]. 光电工程, 2011, 38 (4): 145- 150.
doi: 10.3969/j.issn.1003-501X.2011.04.025 |
TAO Bingjie , HAN Jiale , LI En . A practical pointer meter reading recognition method[J]. Opto-Electronic Engineering, 2011, 38 (4): 145- 150.
doi: 10.3969/j.issn.1003-501X.2011.04.025 |
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2 | 蒋薇.基于图像识别的指针式仪表数据处理终端研究[D].青岛:青岛大学, 2014. |
JIANG Wei. Research on pointer instrument data processing terminal based on image recognition[D]. Qingdao: Qingdao University, 2014. | |
3 | 赵菁.基于图像处理的指针式仪表识别设计[D].西安:西安电子科技大学, 2011. |
ZHAO Jing. Pointer type instrument recognition design based on image processing[D]. Xi′an: Xidian University, 2011. | |
4 |
孙琳, 王永东. 指针式仪表自动检定系统图像识别技术[J]. 现代电子技术, 2011, 34 (8): 101- 104.
doi: 10.3969/j.issn.1004-373X.2011.08.032 |
SUN Lin , WANG Yongdong . Pointer meter automatic verification system image recognition technology[J]. Modern Electronics Technique, 2011, 34 (8): 101- 104.
doi: 10.3969/j.issn.1004-373X.2011.08.032 |
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5 |
徐洋. 基于图像处理的汽车指针仪表检测研究[J]. 计算机应用与软件, 2014, 31 (8): 219- 221.
doi: 10.3969/j.issn.1000-386x.2014.08.054 |
XU Yang . Research on vehicle pointer instrument detection based on image processing[J]. Computer Applications and Software, 2014, 31 (8): 219- 221.
doi: 10.3969/j.issn.1000-386x.2014.08.054 |
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何智杰, 张彬. 高精度指针仪表自动读数识别方法[J]. 计算机辅助工程, 2006, 15 (3): 9- 12.
doi: 10.3969/j.issn.1006-0871.2006.03.003 |
HE Zhijie , ZHANG Bin . High-precision pointer meter automatic reading recognition method[J]. Computer Aided Engineering, 2006, 15 (3): 9- 12.
doi: 10.3969/j.issn.1006-0871.2006.03.003 |
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王瑞, 李琦. 一种基于改进角度法的指针式仪表图像自动读数方法[J]. 电测与仪表, 2013, 50 (11): 115- 118.
doi: 10.3969/j.issn.1001-1390.2013.11.026 |
WANG Rui , LI Qi . Pointer type instrument image automatic reading method based on improved angle method[J]. Electrical Measurement & Instrumentation, 2013, 50 (11): 115- 118.
doi: 10.3969/j.issn.1001-1390.2013.11.026 |
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8 |
朱海霞. 基于改进Hough变换和BP网络的指针仪表识别[J]. 电测与仪表, 2015, 52 (5): 11- 14.
doi: 10.3969/j.issn.1001-1390.2015.05.003 |
ZHU Haixia . Pointer meter recognition based on improved Hough transform and BP network[J]. Electrical Measurement & Instrumentation, 2015, 52 (5): 11- 14.
doi: 10.3969/j.issn.1001-1390.2015.05.003 |
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9 | RE NS , HE K , GIRSHICK R . Faster R-CNN: towards real-time object detection with region proposal networks[J]. IEEE Transactions on Pattern Analysis & Machine Intelligence, 2017, 39 (6): 1440- 1448. |
10 | LIU WEI, ANGUELOV DRAGOMIR, ERHAN DUMITRU. SSD: single shot multibox detector[C]//European Conference on Computer Vision. Berlin, Germany: Springer, 2016: 21-37. |
11 | REDMON JOSEPH, DIVVALA SANTOSH, GIRSHICK ROSS, et al. You only look once: unified, real-time object detection[C]// The IEEE Conference on Computer Vision and Pattern Recognition (CVPR). Seattle, USA: IEEE, 2016: 779-788. |
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13 | RONNEBERGER Olaf, FISCHER Philipp, BROX Thomas. U-Net: convolutional networks for biomedical image segmentation[C]//Medical Image Computing and Computer-Assisted Intervention. Berlin, Germany: Springer, 2015: 234-241. |
14 |
CHEN Liang , PAPANDREOU George , KOKKINOS Iasonas , et al. DeepLab: semantic image segmentation with deep convolutional nets, atrous convolution, and fully connected CRFs[J]. IEEE Transactions on Pattern Analysis and Machine Intelligence, 2018, 40 (4): 834- 848.
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15 | LIN Guosheng, MILAN Anton. RefineNet: multi-path refinement networks for high-resolution semantic segmentation[C]//IEEE Conference on Computer Vision and Pattern. Seattle, USA: IEEE, 2017: 5168-5177. |
16 | PENG Chao, ZHANG Xiangyu, YU Gang, et al. Large kernel matters: improve semantic segmentation by global convolutional network[C]//The IEEE Conference on Computer Vision and Pattern Recognition (CVPR). Seattle, USA: IEEE, 2017: 4353-4361. |
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19 | SIMONYAN K, ZISSERMAN A. Very deep convolutional networks for large-scale image recognition[C]//International Conference on Learning Representations (ICLR). San Diego, USA: ICLR, 2015. |
20 | KINGMA D P, BA J. Adam: a method for stochastic optimization[C]//International Conference on Learning Representations (ICLR). San Diego, USA: ICLR, 2015. |
[1] | ZHANG Zhi-wen,SONG Shi-jun, . Circle locating method based on roundness [J]. JOURNAL OF SHANDONG UNIVERSITY (ENGINEERING SCIENCE), 2006, 36(1): 19-22 . |
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