Journal of Computer Applications ›› 2019, Vol. 39 ›› Issue (6): 1663-1668.DOI: 10.11772/j.issn.1001-9081.2018102190
• Artificial intelligence • Previous Articles Next Articles
LIU Bo, WANG Shengzheng, ZHAO Jiansen, LI Mingfeng
Received:
2018-10-31
Revised:
2019-01-11
Online:
2019-06-17
Published:
2019-06-10
Supported by:
通讯作者:
王胜正
作者简介:
刘博(1992-),男,安徽阜阳人,硕士研究生,主要研究方向:船舶智能航行、计算机视觉;王胜正(1976-),男,湖南双峰人,教授,博士生导师,博士,主要研究方向:航海仿真、智能船舶航行、大数据、机器学习;赵建森(1983-),男,黑龙江海林人,副教授,博士,主要研究方向:智能通信、微波与天线;李明峰(1994-),男,四川遂宁人,硕士研究生,主要研究方向:船舶智能航行、强化学习。
基金资助:
CLC Number:
LIU Bo, WANG Shengzheng, ZHAO Jiansen, LI Mingfeng. Ship tracking and recognition based on Darknet network and YOLOv3 algorithm[J]. Journal of Computer Applications, 2019, 39(6): 1663-1668.
刘博, 王胜正, 赵建森, 李明峰. 基于Darknet网络和YOLOv3算法的船舶跟踪识别[J]. 计算机应用, 2019, 39(6): 1663-1668.
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URL: http://www.joca.cn/EN/10.11772/j.issn.1001-9081.2018102190
[1] 黄于欣.基于openCV的视频路径船舶检测与跟踪[J].舰船科学技术,2017,39(8A):28-30.(HUANG Y X. Ship detection and tracking based on openCV video path[J]. Ship Science and Technology, 2017, 39(8A):28-30. [2] 滕飞,刘清,郭建明,等.TLD框架下的内河船舶跟踪[J].应用科学学报,2014,32(1):105-110.(TENG F, LIU Q, GUO J M, et al. Inland waterway ship tracking using a TLD framework[J]. Journal of Applied Sciences, 2014, 32(1):105-110.) [3] 朱广华.BP神经网络和卡尔曼滤波相结合的船舶运动跟踪[J].舰船科学技术,2016,38(10A):82-84.(ZHU G H. Ship motion tracking based on combination of BP neural network and Kalman filter[J]. Ship Science and Technology, 2016, 38(10A):82-84.) [4] 蒋少峰,王超,吴樊,等.基于结构特征分析的COSMO-SkyMed图像商用船舶分类算法[J].遥感技术与应用,2014,29(4):607-615.(JIANG S F, WANG C, WU F, et al. Algorithm for merchant ship classification in COSMO-SkyMed images based on structural feature analysis[J]. Remote Sensing Technology and Application, 2014, 29(4):607-615.) [5] 胡侯立,魏维,胡蒙娜.深度学习算法的原理及应用[J].信息技术,2015(2):175-177.(HU H L, WEI W, HU M N. Principles and practices of deep learning[J]. Information Technology, 2015(2):175-177.) [6] KRIZHEVSKY A, SUTSKEVER I, HINTON G E. ImageNet classification with deep convolutional neural networks[C]//NIPS 2012:Proceedings of the 25th International Conference on Neural Information Processing Systems. North Miami Beach, FL:Curran Associates Inc., 2012:1097-1105. [7] SZEGEDY C, TOSHEV A, ERHAN D. Deep neural networks for object detection[C]//Proceedings of the 2013 International Conference on Neural Information Processing Systems. Cambridge, MA:MIT Press, 2013:2553-2561. [8] ERHAN D, SZEGEDY C, TOSHEV A, et al. Scalable object detection using deep neural networks[C]//CVPR 2014:Proceedings of the 2014 IEEE Conference on Computer Vision and Pattern Recognition. Washington, DC:IEEE Computer Society, 2014:2155-2162. [9] SERMANET P, EIGEN D, ZHANG X, et al. Overfeat:Integrated recognition, localization and detection using convolutional networks[EB/OL].[2018-08-25]. https://www.nvidia.co.kr/content/tesla/pdf/machine-learning/overfeat-recognition-localication-detection.pdf. [10] GIRSHICK R, DONAHUE J, DARRELL T, et al. Rich feature hierarchies for accurate object detection and semantic segmentation[C]//CVPR 2014:Proceedings of the 2014 IEEE Conference on Computer Vision and Pattern Recognition. Washington, DC:IEEE Computer Society, 2014:580-587. [11] SIMONYAN K, ZISSERMAN A. Very deep convolutional networks for large-scale image recognition[EB/OL].[2018-08-25]. https://arxiv.org/abs/1409.1556. [12] SZEGEDY C, LIU W, JIA Y Q, et al. Going deeper with convolutions[C]//Proceedings of the 2015 IEEE Conference on Computer Vision and Pattern Recognition. Washington, DC:IEEE Computer Society, 2015:1-9. [13] 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 and Machine Intelligence, 2015, 37(9):1904-1916. [14] GIRSHICK R. Fast R-CNN[EB/OL].[2018-08-24]. http://cn.arxiv.org/pdf/1504.08083.pdf. [15] LIU W, ANGUELOV D, ERHAN D, et al. SSD:single shot multibox detector[C]//ECCV 2016:Proceedings of the 2016 European Conference on Computer Vision, LNCS 9905. Cham:Springer, 2016:21-37. [16] REDMON J, DIVVALA S, GIRSHICK R, et al. You only look once:unified, real-time object detection[C]//Proceedings of the 2015 IEEE Conference on Computer Vision and Pattern Recognition. Washington, DC:IEEE Computer Society, 2015:779-788. [17] CHAUHAN A K, KRISHAN P. Moving object tracking using gaussian mixture model and optical flow[J]. International Journal of Advanced Research in Computer Science and Software Engineering, 2013, 3(4):243-246. [18] TRIPATHI R P, GHOSH S, CHANDLE J O. Tracking of object using optimal adaptive Kalman filter[C]//Proceedings of the 2016 IEEE International Conference on Engineering and Technology. Piscataway, NJ:IEEE, 2016:17-18. [19] 翟卫欣,程承旗.基于Kalman滤波的Camshift运动跟踪算法[J].北京大学学报(自然科学版),2015,51(5):799-804.(ZHAI W X, CHENG C Q. A Camshift motion tracking algorithm based on Kalman filter[J]. Acta Scientiarum Naturalium Universitatis Pekinensis, 2015, 51(5):799-804.) [20] FANG J, ZHOU Y, YU Y, et al. Fine-grained vehicle model recognition using a coarse-to-fine convolutional neural network architecture[J]. IEEE Transactions on Intelligent Transportation Systems, 2017, 18(7):1782-1792. [21] 张舞杰,李迪,叶峰.基于Sigmoid函数拟合的亚像素边缘检测方法[J].华南理工大学学报(自然科学版),2009,37(10):39-43.(ZHANG W J, LI D, YE F. Sub-pixel edge detection method based on Sigmoid function fitting[J].Journal of South China University of Technology (Natural Science Edition), 2009, 37(10):39-43.) [22] CHEN X Q, WANG S Z, SHI C J, et al. Robust ship tracking via multi-view learning and sparse representation[J]. Journal of Navigation, 2019, 72(1):176-192. |
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