Journal of Shandong University(Engineering Science) ›› 2019, Vol. 49 ›› Issue (5): 98-104.doi: 10.6040/j.issn.1672-3961.0.2018.348
• Machine Learning & Data Mining • Previous Articles Next Articles
CLC Number:
1 | 薛瑞.基于RGB-D数据的点云配准[D].西安:长安大学, 2017. |
XUE Rui. Point cloud registration based on RGB-D data[D]. Xi'an: Chang'an University, 2017. | |
2 | 赵熙.基于地面激光扫描面点云数据的三维重建方法研究[D].武汉:武汉大学, 2010. |
ZHAO Xi. Research on 3D reconstruction method based on surface laser scanning point cloud data[D]. Wuhan: Wuhan University, 2010. | |
3 | MATURAN D, SCHERER S. VoxNet: a 3D convolutional neural network for real-time object recognition[C]//2015 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS). Hamburg, Germany: IEEE Press, 2015: 922-928. |
4 | WU Z, SONG S, KHOSLA A, et al. 3d shapenets: a deep representation for volumetric shapes[C]//Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition. Boston, USA: IEEE Press, 2015: 1912-1920. |
5 | LI B. 3D fully convolutional network for vehicle detection in point cloud[C]//2017 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS). Vancouver, Canada: IEEE Press, 2017: 1513-1518. |
6 | WANG D Z, POSNER I, WANG D Z, et al. Voting for voting in online point cloud object detection[C]//Robotics: Science and Systems. Rome, Italy: IEEE Press, 2015: 1317-1325. |
7 | ENGELCKE M , RAO D , WANG D Z , et al. Vote3Deep: fast object detection in 3D point clouds using efficient convolutional neural networks[J]. ICRA, 2016, 1609, 1355- 1361. |
8 | LONG J , SHELHAMER E , DARRELL T . Fully convolutional networks for semantic segmentation[J]. IEEE Transactions on Pattern Analysis & Machine Intelligence, 2017, 39 (4): 640- 651. |
9 | QI C R, SU H, NIWBNER M, et al. Volumetric and multi-view cnns for object classification on 3d data[C]//Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition. Las Vegas, USA: IEEE Press, 2016: 5648-5656. |
10 | SU H, MAJI S, KALOGERAKIS E, et al. Multi-view convolutional neural networks for 3d shape recognition[C]//Proceedings of the IEEE International Conference on Computer Vision. Santiago, Chile: IEEE Press, 2015: 945-953. |
11 | LI B, ZHANG T, XIA T. Vehicle detection from 3D lidar using fully convolutional network[C]//Robotics: Science and System. Ann Arbor, USA: IEEE Press, 2016: 1608-1616. |
12 | CHEN X , MA H , WAN J , et al. Multi-view 3D object detection network for autonomous driving[J]. Computer Vision and Pattern Recognition(CVPR), 2016, (10): 6526- 6534. |
13 |
GONZALEZ A , VAZQUEZ D , LOPEZ A M , et al. On-board object detection: Multicue, multimodal, and multiview random forest of local experts[J]. IEEE Transactions on Cybernetics, 2017, 47 (11): 3980- 3990.
doi: 10.1109/TCYB.2016.2593940 |
14 |
ENZWEILER M , GAVRILA D M . A multilevel mixture-of-experts framework for pedestrian classification[J]. Image Processing IEEE Transactions, 2011, 20 (10): 2967- 2979.
doi: 10.1109/TIP.2011.2142006 |
15 | QI C R, LIU W, WU C, et al. Frustum pointnets for 3d object detection from rgb-d data[C]//Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition. Salt Lake City, USA: IEEE Press, 2018: 918-927. |
16 | CHARLES R Q, SU H, MO K, et al. Pointnet: Deep learning on point sets for 3d classification and segmentation[C]//Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition. Honolulu, USA: IEEE Press, 2017: 652-660. |
17 | GEIGER A, LENZ P, URTASUN R. Are we ready for autonomous driving: the KITTI vision benchmark suite[C]//IEEE Conference on Computer Vision and Pattern Recognition. Providence, USA: IEEE Computer Society, 2012: 3354-3361. |
18 |
GEIGER A , LENZ P , STILLER C , et al. Vision meets robotics: the KITTI dataset[J]. International Journal of Robotics Research, 2013, 32 (11): 1231- 1237.
doi: 10.1177/0278364913491297 |
19 | ZHOU Y, TUZEL O. Voxelnet: end-to-end learning for point cloud based 3d object detection[C]//Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition. Salt Lake City, USA: IEEE Press, 2018: 4490-4499. |
20 | KU J, MOZIFIAN M, LEE J, et al. Joint 3d proposal generation and object detection from view aggregation[C]//2018 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS). Madrid, Spain: IEEE Press, 2018: 1-8. |
[1] | Ji ZHANG,Cui JIN,Hongyuan WANG,Shoubing CHEN. Pedestrian recognition based on singular value decomposition pedestrian alignment network [J]. Journal of Shandong University(Engineering Science), 2019, 49(5): 91-97. |
[2] | Zhixiang LIANG,Xiaoming LIU,Ying MU,Yutian LIU. Prediction method of wind power and PV ramp event based on deep learning [J]. Journal of Shandong University(Engineering Science), 2019, 49(5): 24-28. |
[3] | Yutian LIU,Runjia SUN,Hongtao WANG,Xueping GU. Review on application of artificial intelligence in power system restoration [J]. Journal of Shandong University(Engineering Science), 2019, 49(5): 1-8. |
[4] | Lizhao LI,Guoyong CAI,Jiao PAN. A microblog rumor events detection method based on C-GRU [J]. Journal of Shandong University(Engineering Science), 2019, 49(2): 102-106, 115. |
[5] | Xiaoxiong HOU,Xinzheng XU,Jiong ZHU,Yanyan GUO. Computer aided diagnosis method for breast cancer based on AlexNet and ensemble classifiers [J]. Journal of Shandong University(Engineering Science), 2019, 49(2): 74-79. |
[6] | Chengbin ZHANG,Hui ZHAO,Zongyu CAO. The vulnerability mining method for KWP2000 protocol based on deep learning and fuzzing [J]. Journal of Shandong University(Engineering Science), 2019, 49(2): 17-22. |
[7] | XIE Zhifeng, WU Jiaping, MA Lizhuang. Chinese financial news classification method based on convolutional neural network [J]. JOURNAL OF SHANDONG UNIVERSITY (ENGINEERING SCIENCE), 2018, 48(3): 34-39. |
[8] | TANG Leshuang, TIAN Guohui, HUANG Bin. An object fusion recognition algorithm based on DSmT [J]. JOURNAL OF SHANDONG UNIVERSITY (ENGINEERING SCIENCE), 2018, 48(1): 50-56. |
[9] | ZHOU Funa, GAO Yulin, WANG Jiayu, WEN Chenglin. Early diagnosis and life prognosis for slowlyvarying fault based on deep learning [J]. JOURNAL OF SHANDONG UNIVERSITY (ENGINEERING SCIENCE), 2017, 47(5): 30-37. |
[10] | HUI Kaifa, CHENG Keyang, ZHAN Yongzhao. The video synopsis based on the enhanced ViBe algorithm [J]. JOURNAL OF SHANDONG UNIVERSITY (ENGINEERING SCIENCE), 2017, 47(3): 43-48. |
[11] | LIU Yingxia, WANG Xichang, TANG Xiaoli, CHANG Faliang. Object detection algorithm based on Bayesian probability estimation in wavelet domain [J]. JOURNAL OF SHANDONG UNIVERSITY (ENGINEERING SCIENCE), 2017, 47(2): 63-70. |
[12] | HE Zhengyi, ZENG Xianhua, QU Shengwei, WU Zhilong. The time series prediction model based on integrated deep learning [J]. JOURNAL OF SHANDONG UNIVERSITY (ENGINEERING SCIENCE), 2016, 46(6): 40-47. |
[13] | ZHENG Yi, ZHU Chengzhang. A prediction method of atmospheric PM2.5 based on DBNs [J]. JOURNAL OF SHANDONG UNIVERSITY (ENGINEERING SCIENCE), 2014, 44(6): 19-25. |
[14] | QIAO Wei1, WANG Hui-yuan1,2, WU Xiao-juan1, LIU Peng-wei1. Crowd object detection and classification based on a chaotic dynamic model [J]. JOURNAL OF SHANDONG UNIVERSITY (ENGINEERING SCIENCE), 2010, 40(2): 19-23. |
|