[1] |
王志宏, 杨震 . 人工智能技术研究及未来智能化信息服务体系的思考[J]. 电信科学, 2017,33(5): 1-11.
|
|
WANG Z H , YANG Z . Research on artificial intelligence technology and the future intelligent information service architecture[J]. Telecommunications Science, 2017,33(5): 1-11.
|
[2] |
窦兰秋 . 浅谈高压输电线路设计工作中应注意的要点[J]. 通讯世界, 2016(10): 203-204.
|
|
DOU L Q . Talking about the key points in the design of high voltage transmission line[J]. Communication World, 2016(10): 203-204.
|
[3] |
赵振兵, 孔英会, 戚银城 ,等. 面向智能输变电的图像处理技术[M]. 北京: 中国电力出版社, 2014.
|
|
ZHAO Z B , KONG Y H , QI Y C ,et al. Image processing technology for intelligent power transmission and transformation[M]. Beijing: China Electric Power PressPress, 2014.
|
[4] |
DALAL N , TRIGGS B . Histograms of oriented gradients for human detection[C]// International Conference on computer vision & Pattern Recognition (CVPR’05). Piscataway:IEEE Press, 2005: 886-893.
|
[5] |
LOWE D G . Distinctive image features from scale-invariant keypoints[J]. International Journal of Computer Vision, 2004,60(2): 91-110.
|
[6] |
BAY H , ESS A , TUYTELAARS T ,et al. Speeded-up robust features (SURF)[J]. Computer Vision and Image Understanding, 2008,110(3): 346-359.
|
[7] |
LIENHART R , MAYDT J . An extended set of haar-like features for rapid object detection[C]// International Conference on Image Processing. Piscataway:IEEE Press, 2002.
|
[8] |
翟永杰, 王迪, 伍洋 ,等. 基于骨架提取的航拍绝缘子图像分步识别方法[J]. 华北电力大学学报(自然科学版), 2015,42(3): 105-110.
|
|
ZHAI Y J , WANG D , WU Y ,et al. Multistep recognition method of aerial insulator image based on skeleton extraction[J]. Journal of North China Electric Power University (Natural Science), 2015,42(3): 105-110.
|
[9] |
班孝坤, 韩军, 陆冬明 ,等. 自然场景中基于局部轮廓特征的类圆对象识别方法[J]. 计算机应用, 2016,36(5): 1399-1403.
|
|
BAN X K , HAN J , LU D M ,et al. Circle like object recognition method based on local contour feature in natural scene[J]. Computer Application, 2016,36(5): 1399-1403.
|
[10] |
KRIZHEVSKY A , SUTSKEVER I , HINTON G E . Imagenet classification with deep convolutional neural networks[J]. Advances in Neural Information Processing Systems, 2012: 1097-1105.
|
[11] |
GIRSHICK R , DONAHUE J , DARRELL T ,et al. Rich feature hierarchies for accurate object detection and semantic segmentation[C]// Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition. Piscataway:IEEE Press, 2014: 580-587.
|
[12] |
REN S , HE K , GIRSHICK R ,et al. Faster R-CNN:towards real-time object detection with region proposal networks[C]// Neural Information Processing Systems. Piscataway:IEEE Press, 2015.
|
[13] |
REDMON J , DIVVALA S , GIRSHICK R ,et al. You only look once:Unified,real-time object detection[C]// IEEE Conference on Computer Vision and Pattern Recognition.[S.l.:s.n. ], 2016: 779-788.
|
[14] |
LIU W , ANGUELOV D , ERHAN D ,et al. SSD:single shot multibox detector[C]// European Conference on Computer Vision. Piscataway:IEEE Press, 2016: 21-37.
|
[15] |
王万国, 田兵, 刘越 ,等. 基于 RCNN 的无人机巡检图像电力小部件识别研究[J]. 地球信息科学学报, 2017,19(2): 256-263.
|
|
WANG W G , TIAN B , LIU Y ,et al. Research on recognition of power widget in UAV Inspection Image based on RCNN[J]. Journal of Earth Information Science, 2017,19(2): 256-263.
|
[16] |
FELZENSZWALB P F , GIRSHICK R B , MCALLESTER D ,et al. Object detection with discriminatively trained part-based models[J]. IEEE Transactions on Pattern Analysis and Machine Intelligence, 2010,32(9): 1627-1645
|
[17] |
HE K , ZHANG X , REN S ,et al. Spatial pyramid pooling in deep convolutional networks for visual recognition[J]. IEEE Transactions on Pattern Analysis and Machine Intelligence, 2015,37(9): 1904-1916.
|
[18] |
汤踊, 韩军, 魏文力 ,等. 深度学习在输电线路中部件识别与缺陷检测的研究[J]. 电子测量技术, 2018,41(6): 60-65.
|
|
TANG Y , HAN J , WEI W L ,et al. Research on component identification and defect detection in transmission line based on deep learning[J]. Electronic Measurement Technology, 2018,41(6): 60-65.
|
[19] |
ARTHUR D , VASSILVITSKII S . K-means++:the advantages of careful seeding[C]// The Eighteenth Annual ACM-SIAM Symposium on Discrete Algorithms. New York:ACM Press, 2007.
|
[20] |
GIRSHICK R , . Fast R-CNN[C]// The IEEE International Conference on Computer Vision (ICCV).[S.l.:s.n]. 2015.
|
[21] |
SIMONYAN K , ZISSERMAN A . Very deep convolutional networks for large-scale image recognition[J]. arXiv:1409.1556, 2014
|
[22] |
HE K , ZHANG X , REN S ,et al. Deep residual learning for image recognition[J]. arXiv:1512.03385,
|
[23] |
HOWARD A G , ZHU M , CHEN B ,et al. MobileNets:efficient convolutional neural networks for mobile vision applications[Z]. 2017
|