Journal of Jilin University(Engineering and Technology Edition) ›› 2023, Vol. 53 ›› Issue (11): 3214-3220.doi: 10.13229/j.cnki.jdxbgxb.20220772
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1 | 潘德伦, 冀隽, 张跃进. 基于运动矢量空间编码的视频监控动态目标检测方法[J]. 吉林大学学报: 工学版, 2021, 51(4): 1370-1374. |
Pan De-lun, Ji Jun, Zhang Yue-jin. Dynamic object detection method of video surveillance based on motion vector space coding[J]. Journal of Jilin University(Engineering and Technology Edition), 2021, 51(4): 1370-1374. | |
2 | 刘伟, 郝晓丽, 吕进来. 自适应混合高斯建模的高效运动目标检测[J]. 中国图象图形学报, 2020, 25(1): 113-125. |
Liu Wei, Hao Xiao-li, Lv Jin-lai. Efficient moving targets detection based on adaptive Gaussian mixture modelling[J]. Journal of Image and Graphics, 2020, 25(1): 113-125. | |
3 | 左军辉, 贾振红, 杨杰, 等. 基于改进背景减法的视频图像运动目标检测[J]. 计算机工程与设计, 2020, 41(5): 1367-1372. |
Zuo Jun-hui, Jia Zhen-hong, Yang Jie, et al. Moving object detection in video image based on improved background subtraction[J]. Computer Engineering and Design, 2020, 41(5): 1367-1372. | |
4 | 闫贺, 黄佳, 李睿安. 基于改进快速区域卷积神经网络的视频SAR运动目标检测算法研究[J]. 电子与信息学报, 2021, 43(3): 615-622. |
Yan He, Huang Jia, Li Rui-an. Research on video SAR moving target detection algorithm based on improved faster region-based CNN[J]. Journal of Electronics & Information Technology, 2021, 43(3): 615-622. | |
5 | 徐武, 唐文权, 郭兴. 混合高斯模型结合五帧差分的运动目标检测[J]. 小型微型计算机系统, 2021, 42(4): 785-790. |
Xu Wu, Tang Wen-quan, Guo Xing. Moving target detection based on hybrid Gaussian model and five frame difference[J]. Journal of Chinese Computer Systems, 2021, 42(4): 785-790. | |
6 | 张小艳, 郭海涛. 基于改进混合高斯模型的井下目标检测算法[J]. 工矿自动化, 2021, 47(4): 67-72. |
Zhang Xiao-yan, Guo Hai-tao. Underground target detection algorithm based on improved Gaussian mixture model[J]. Industry and Mine Automation, 2021, 47(4): 67-72. | |
7 | 尹芳, 孟迪, 李骜. 改进ViBe的运动目标检测算法[J]. 哈尔滨理工大学学报, 2022, 27(1): 23-30. |
Yin Fang, Meng Di, Li Ao. Improvement algorithm of ViBe in moving target detection[J]. Journal of Harbin University of Science and Technology, 2022, 27(1): 23-30. | |
8 | 曲优, 李文辉. 基于锚框变换的单阶段旋转目标检测方法[J]. 吉林大学学报: 工学版, 2022, 52(1): 162-173. |
Qu You, Li Wen-hui. Single-stage rotated object detection network based on anchor transformation[J]. Journal of Jilin University(Engineering and Technology Edition), 2022, 52(1): 162-173. | |
9 | 哈艳, 袁伟珵, 孟翔杰. 基于增强图卷积神经网络的病毒形态识别方法研究[J]. 中国全科医学, 2022, 25(14): 1749-1756. |
Yan Ha, Yuan Wei-cheng, Meng Xiang-jie. Research on virus morphology recognition method based on enhanced graph convolutional network[J]. Chinese General Practice, 2022, 25(14): 1749-1756. | |
10 | 李朝献. 基于自适应三维立体图像增强优化处理研究[J]. 计算机仿真, 2020, 37(12): 358-361. |
Li Chao-xian. Research on optimization of 3D image enhancement based on adaptive[J]. Computer Simulation, 2020, 37(12): 358-361. | |
11 | 涂继辉, 杜红, 眭海刚. 高分辨率航空影像阴影自动检测和去除[J]. 遥感信息, 2020, 35(2): 38-45. |
Tu Ji-hui, Du Hong, Sui Hai-gang. Automatic shadow detection and removal in high resolution aerial imagery[J]. Remote Sensing Information, 2020, 35(2): 38-45. | |
12 | 王文举, 王江薇. 光谱反射率重建技术的研究进展[J]. 包装工程, 2020, 41(11): 254-261. |
Wang Wen-ju, Wang Jiang-wei. Research progress of spectral reflectance reconstruction technology[J]. Packaging Engineering, 2020, 41(11): 254-261. | |
13 | 马巧梅, 王明俊, 梁昊然. 复杂场景下基于改进YOLOv3的车牌定位检测算法[J]. 计算机工程与应用, 2021, 57(7): 198-208. |
Ma Qiao-mei, Wang Ming-jun, Liang Hao-ran. License plate location detection algorithm based on improved YOLOv3 in complex scenes[J]. Computer Engineering and Applications, 2021, 57(7): 198-208. | |
14 | 彭继慎, 孙礼鑫, 王凯. 基于模型压缩的ED-YOLO电力巡检无人机避障目标检测算法[J]. 仪器仪表学报, 2021, 42(10): 161-170. |
Peng Ji-shen, Sun Li-xin, Wang Kai. ED-YOLO power inspection UAV obstacle avoidance target detection algorithm based on model compression[J]. Chinese Journal of Scientific Instrument, 2021, 42(10): 161-170. | |
15 | 宋艳艳, 谭励, 马子豪. 改进YOLOV3算法的视频目标检测[J]. 计算机科学与探索, 2021, 15(1): 163-172. |
Song Yan-yan, Tan Li, Ma Zi-hao. Video target detection based on improved YOLOV3 algorithm[J]. Journal of Frontiers of Computer Science & Technology, 2021, 15(1): 163-172. |
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