激光与光电子学进展, 2020, 57 (10): 101010, 网络出版: 2020-05-08   

基于改进YOLOv2模型的多目标识别方法 下载: 983次

Multi-Target Recognition Method Based on Improved YOLOv2 Model
作者单位
1 西安工程大学电子信息学院, 陕西 西安 710048
2 西安计量技术研究院, 陕西 西安 710068
引用该论文

李珣, 时斌斌, 刘洋, 张蕾, 王晓华. 基于改进YOLOv2模型的多目标识别方法[J]. 激光与光电子学进展, 2020, 57(10): 101010.

Xun Li, Binbin Shi, Yang Liu, Lei Zhang, Xiaohua Wang. Multi-Target Recognition Method Based on Improved YOLOv2 Model[J]. Laser & Optoelectronics Progress, 2020, 57(10): 101010.

参考文献

[1] 王得成, 陈向宁, 赵峰, 等. 基于卷积神经网络和RGB-D图像的车辆检测算法[J]. 激光与光电子学进展, 2019, 56(18): 181003.

    Wang D C, Chen X N, Zhao F, et al. Vehicle detection algorithm based onconvolutional neural network and RGB-D images[J]. Laser & Optoelectronics Progress, 2019, 56(18): 181003.

[2] 华夏, 王新晴, 王东, 等. 基于改进SSD的交通大场景多目标检测[J]. 光学学报, 2018, 38(12): 1215003.

    Hua X, Wang X Q, Wang D, et al. Multi-objective detection of traffic scenes based on improved SSD[J]. Acta Optica Sinica, 2018, 38(12): 1215003.

[3] 屈治华, 邵毅明, 邓天民, 等. 复杂光照条件下的交通标志检测与识别[J]. 激光与光电子学进展, 2019, 56(23): 231009.

    Qu Z H, Shao Y M, Deng T M, et al. Traffic sign detection and recognition under complicated lighting conditions[J]. Laser & Optoelectronics Progress, 2019, 56(23): 231009.

[4] 张敦凤, 高宁化, 王姮, 等. 基于分块LBP融合特征和SVM的人脸识别算法[J]. 传感器与微系统, 2019, 38(5): 154-156, 160.

    Zhang D F, Gao N H, Wang H, et al. Face recognition algorithm based on block LBP fusion feature and SVM[J]. Transducer and Microsystem Technologies, 2019, 38(5): 154-156, 160.

[5] 郭健. 基于局部特征的图像匹配算法研究[D]. 南京: 南京邮电大学, 2018.

    GuoJ. Research of image matching algorithm based on local features[D]. Nanjing: Nanjing University of Posts and Telecommunications, 2018.

[6] 王文秀, 傅雨田, 董峰, 等. 基于深度卷积神经网络的红外船只目标检测方法[J]. 光学学报, 2018, 38(7): 0712006.

    Wang W X, Fu Y T, Dong F, et al. Infrared ship target detection method based on deep convolution neural network[J]. Acta Optica Sinica, 2018, 38(7): 0712006.

[7] 金立生, 王岩, 刘景华, 等. 基于Adaboost算法的日间前方车辆检测[J]. 吉林大学学报(工学版), 2014, 44(6): 1604-1608.

    Jin L S, Wang Y, Liu J H, et al. Front vehicle detection based on Adaboost algorithm in daytime[J]. Journal of Jilin University(Engineering and Technology Edition), 2014, 44(6): 1604-1608.

[8] 郑武兴, 王春平, 付强. 改进的KCF红外空中目标跟踪方法[J]. 激光与红外, 2017, 47(12): 1553-1558.

    Zheng W X, Wang C P, Fu Q. Improved KCF infrared aerial target tracking method[J]. Laser & Infrared, 2017, 47(12): 1553-1558.

[9] 赵恒, 安维胜. 结合深度学习的图像显著目标检测[J]. 激光与光电子学进展, 2018, 55(12): 121003.

    Zhao H, An W S. Image salient object detection combined with deep learning[J]. Laser & Optoelectronics Progress, 2018, 55(12): 121003.

[10] GirshickR, DonahueJ, DarrellT, et al. Rich feature hierarchies for accurate object detection and semantic segmentation[C]∥2014 IEEE Conference on Computer Vision and Pattern Recognition, June 23-28, 2014. Columbus, OH, USA. New York: IEEE, 2014: 8- 13.

[11] 李云鹏, 侯凌燕, 王超. 基于YOLOv2的复杂场景下车辆目标检测[J]. 电视技术, 2018, 42(5): 100-106.

    Li Y P, Hou L Y, Wang C. Vehicle object detection in complex scene based on YOLOv2[J]. Video Engineering, 2018, 42(5): 100-106.

[12] 张琦, 胡广地, 李雨生, 等. 改进Fast-RCNN的双目视觉车辆检测方法[J]. 应用光学, 2018, 39(6): 832-838.

    Zhang Q, Hu G D, Li Y S, et al. Binocular vision vehicle detection method based on improved Fast-RCNN[J]. Journal of Applied Optics, 2018, 39(6): 832-838.

[13] 冯小雨, 梅卫, 胡大帅. 基于改进Faster R-CNN的空中目标检测[J]. 光学学报, 2018, 38(6): 0615004.

    Feng X Y, Mei W, Hu D S. Aerialtarget detection based on improved faster R-CNN[J]. Acta Optica Sinica, 2018, 38(6): 0615004.

[14] RedmonJ, DivvalaS, GirshickR, et al. You only look once: unified, real-time object detection[C]∥2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR), June 27-30, 2016. Las Vegas, NV, USA. New York: IEEE, 2016: 779- 788.

[15] LiuW, AnguelovD, ErhanD, et al.SSD:single shot multibox detector[M] ∥Computer Vision-ECCV 2016. Cham: Springer International Publishing, 2016: 21- 37.

[16] 宋焕生, 张向清, 郑宝峰, 等. 基于深度学习方法的复杂场景下车辆目标检测[J]. 计算机应用研究, 2018, 35(4): 1270-1273.

    Song H S, Zhang X Q, Zheng B F, et al. Vehicle detection based on deep learning in complex scene[J]. Application Research of Computers, 2018, 35(4): 1270-1273.

[17] 朱明明, 许悦雷, 马时平, 等. 改进区域卷积神经网络的机场检测方法[J]. 光学学报, 2018, 38(7): 0728001.

    Zhu M M, Xu Y L, Ma S P, et al. Airport detection method with improved region-based convolutional neural network[J]. Acta Optica Sinica, 2018, 38(7): 0728001.

[18] 陆星家, 郭璘, 陈志荣, 等. 基于外观和运动的车辆检测和追踪算法研究[J]. 计算机工程, 2014, 40(8): 152-157.

    Lu X J, Guo L, Chen Z R, et al. Study on vehicle detection and tracking algorithms based on appearance and motion[J]. Computer Engineering, 2014, 40(8): 152-157.

[19] 李珣, 刘瑶, 李鹏飞, 等. 基于Darknet框架下YOLO v2算法的车辆多目标检测方法[J]. 交通运输工程学报, 2018, 18(6): 142-158.

    Li X, Liu Y, Li P F, et al. Vehicle multi-target detection method based on YOLO v2 algorithm under darknet framework[J]. Journal of Traffic and Transportation Engineering, 2018, 18(6): 142-158.

[20] 李明, 景军锋, 李鹏飞. 应用GAN和Faster R-CNN的色织物缺陷识别[J]. 西安工程大学学报, 2018, 32(6): 663-669.

    Li M, Jing J F, Li P F. Yarn-dyed fabric defect detection based on GAN and Faster R-CNN[J]. Journal of Xi'an Polytechnic University, 2018, 32(6): 663-669.

[21] LiX, LiuY, Zhao ZF, et al. A deep learning approach of vehicle multitarget detection from traffic video[J]. Journal of Advanced Transportation, 2018( 11): 1- 11.

李珣, 时斌斌, 刘洋, 张蕾, 王晓华. 基于改进YOLOv2模型的多目标识别方法[J]. 激光与光电子学进展, 2020, 57(10): 101010. Xun Li, Binbin Shi, Yang Liu, Lei Zhang, Xiaohua Wang. Multi-Target Recognition Method Based on Improved YOLOv2 Model[J]. Laser & Optoelectronics Progress, 2020, 57(10): 101010.

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