{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,11,28]],"date-time":"2025-11-28T05:01:38Z","timestamp":1764306098703,"version":"3.37.3"},"reference-count":29,"publisher":"Springer Science and Business Media LLC","issue":"1","license":[{"start":{"date-parts":[[2024,1,19]],"date-time":"2024-01-19T00:00:00Z","timestamp":1705622400000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2024,1,19]],"date-time":"2024-01-19T00:00:00Z","timestamp":1705622400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"}],"funder":[{"DOI":"10.13039\/100007847","name":"Natural Science Foundation of Jilin Province of China","doi-asserted-by":"crossref","award":["YDZJ202201ZYTS655"],"award-info":[{"award-number":["YDZJ202201ZYTS655"]}],"id":[{"id":"10.13039\/100007847","id-type":"DOI","asserted-by":"crossref"}]}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["J Grid Computing"],"published-print":{"date-parts":[[2024,3]]},"DOI":"10.1007\/s10723-023-09736-0","type":"journal-article","created":{"date-parts":[[2024,1,19]],"date-time":"2024-01-19T09:02:38Z","timestamp":1705654958000},"update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":1,"title":["3D Lidar Target Detection Method at the Edge for the Cloud Continuum"],"prefix":"10.1007","volume":"22","author":[{"given":"Xuemei","family":"Li","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Xuelian","family":"Liu","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Da","family":"Xie","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Chong","family":"Chen","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2024,1,19]]},"reference":[{"key":"9736_CR1","doi-asserted-by":"crossref","unstructured":"Girshick, R., Donahue, J., Darrell, T., Malik, J.: Rich feature hierarchies for accurate target detection and semantic segmentation. Tech Report 1311. 2524v5 (2014)","DOI":"10.1109\/CVPR.2014.81"},{"key":"9736_CR2","doi-asserted-by":"crossref","unstructured":"Redmon, J., Divvala, S., Girshick, R., Farhadi, A.: You Only Look Once: Unified, Real-Time target detection. The IEEE Conference on Computer Vision and Pattern Recognition, 779\u2013788 (2016)","DOI":"10.1109\/CVPR.2016.91"},{"key":"9736_CR3","doi-asserted-by":"crossref","unstructured":"Redmon, J., Farhadi, A.: YOLO9000: Better, Faster, Stronger, Proceedings of the IEEE conference oncomputer vision and pattern recognition (2017)","DOI":"10.1109\/CVPR.2017.690"},{"key":"9736_CR4","first-page":"00600","volume":"1604","author":"T Kong","year":"2016","unstructured":"Kong, T., Yao, A.B., Chen, Y.R., Sun, F.C.: HyperNet: Towards Accurate Region Proposal Generation and target detection. IEICE Trans. Fundam. Electron. Commun. Comput. Sci. 1604, 00600 (2016)","journal-title":"IEICE Trans. Fundam. Electron. Commun. Comput. Sci."},{"key":"9736_CR5","doi-asserted-by":"crossref","unstructured":"Liu, W., Anguelov, D., Erhan, D., Szegedy, C., Reed, S., Fu, C. Y., Berg, A. C.: SSD: Single shot multibox detector. European Conference on Computer vision, 21\u201337 (2016)","DOI":"10.1007\/978-3-319-46448-0_2"},{"key":"9736_CR6","doi-asserted-by":"crossref","unstructured":"Charles, R. Q., Hao, S., Mo, K., Guibas, L.J.: Pointnet: Deep learning on point sets for 3d classification and segmentation. The IEEE Conference on Computer Vision and Pattern Recognition (2017)","DOI":"10.1109\/CVPR.2017.16"},{"key":"9736_CR7","unstructured":"Charles, R. Q., Li, Y., Hao, S., Guibas, L. J.; Pointnet++: Deep hierarchical feature learning on point sets in a metric space. Advances in Neural Information Processing Systems (2017)"},{"key":"9736_CR8","doi-asserted-by":"crossref","unstructured":"Chen, X., Ma, H., Wan, J ., Li, B., Xia, T. ; Multi-view 3D target detection network for autonomous driving. The IEEE Conference on Computer Vision and Pattern Recognition, 1907\u20131915 (2017)","DOI":"10.1109\/CVPR.2017.691"},{"key":"9736_CR9","unstructured":"Li, Y. Y., Bu, R., Sun, M. C., Wu, W., Di, X H., Chen, B.Q.: PointCNN: Convolution On X-Transformed Points. 32th Conference and Workshop on Neural Information Processing Systems (2018)"},{"key":"9736_CR10","doi-asserted-by":"crossref","unstructured":"Fu, J., Liu, J. , Tian, H. J., Li, Y., Bao, Y. J., Fang, Z. W., Lu, H.Q.: Dual Attention Network for Scene Segmentation. The IEEE Conference on Computer Vision and Pattern Recognition, 02983v4 (2018)","DOI":"10.1109\/CVPR.2019.00326"},{"issue":"10","key":"9736_CR11","doi-asserted-by":"publisher","first-page":"3337","DOI":"10.3390\/s18103337","volume":"18","author":"Y Yan","year":"2018","unstructured":"Yan, Y., Mao, Y.X., Li, B.: SECOND: Sparsely Embedded Convolutional Detection. Sensors 18(10), 3337 (2018)","journal-title":"Sensors"},{"key":"9736_CR12","unstructured":"Liu, Z. J., Tang, H. T., Lin, Y. J., Han, S. : Point-Voxel CNN for Efficient 3D Deep Learing. Thirty-third Conference on Neural Information Processing Systems (2019)"},{"key":"9736_CR13","doi-asserted-by":"crossref","unstructured":"Wang, Z ., Jia, K. : Frustum convnet: Sliding frustums to aggregate local point-wise features for a modal 3D target detection. International Conference on Intelligent Robots and Systems. 1742\u20131749 (2019)","DOI":"10.1109\/IROS40897.2019.8968513"},{"key":"9736_CR14","doi-asserted-by":"crossref","unstructured":"Caesar, H., Bankiti, V., Lang, A. H., Vora, S., Liong, V.E., Xu, Q., Krishnan, A., Pan, Y., Baldan, G., Beijbom, O.: nuScenes: A multimodal dataset for autonomous driving. The IEEE Conference on Computer Vision and Pattern Recognition. 11618\u201311628 (2020)","DOI":"10.1109\/CVPR42600.2020.01164"},{"key":"9736_CR15","doi-asserted-by":"crossref","unstructured":"Halloran, B., Premaratne, P., Vial, P.J.: Robust one-dimensional calibration and localisation of a distributed camera sensor network. Pattern Recognition. 107058 (2020)","DOI":"10.1016\/j.patcog.2019.107058"},{"key":"9736_CR16","unstructured":"Srinivas, A., Laskin, M., Abbeel, P. : CURL: Contrastive Unsupervised Representations for Reinforcement Learning. 2004.04136v4 (2020)"},{"key":"9736_CR17","doi-asserted-by":"crossref","unstructured":"He, C. H., Zeng, H., Huang, J.Q., Hua, X.S., Zhang, L. : Structure aware single stage 3D target detection from point cloud. The IEEE Conference on Computer Vision and Pattern Recognition. 11870\u201311879 (2020)","DOI":"10.1109\/CVPR42600.2020.01189"},{"key":"9736_CR18","doi-asserted-by":"crossref","unstructured":"Liu, Y., Wang, L., Liu, M. ; YOLOStereo3D: A step back to 2D for efficient stereo 3D detection. International Conference on Robotics and Automation. 13018\u201313024.770\u2013779 (2021)","DOI":"10.1109\/ICRA48506.2021.9561423"},{"key":"9736_CR19","doi-asserted-by":"crossref","unstructured":"Zhou, J., Hu, Y.Y. , Huang, X.Y., Wang, T. J. : Three-dimensional object detection network based on geometric information supplement strategy. Computers & Electrical Engineering. 108577 (2023)","DOI":"10.1016\/j.compeleceng.2023.108577"},{"key":"9736_CR20","doi-asserted-by":"crossref","unstructured":"Liu, X.Y., Zhang, B.F., Liu, N. : The Graph Neural Network Detector Based on Neighbor Feature Alignment Mechanism in LIDAR Point Clouds. Machines. 11010116 (2023)","DOI":"10.3390\/machines11010116"},{"key":"9736_CR21","doi-asserted-by":"crossref","unstructured":"Zhou, Y., Tuzel, O. : Voxelnet: End-end learning for point cloud based 3d target detection. The IEEE Conference on Computer Vision and Pattern Recognition. 4490\u20134499 (2018)","DOI":"10.1109\/CVPR.2018.00472"},{"key":"9736_CR22","doi-asserted-by":"crossref","unstructured":"Lang, A. H., Vora, S., Caesar, H., Zhou, L.B., Yang, J., Beijbom, O. : Pointpillars: Fast encoders for target detection from point clouds.The IEEE Conference on Computer Vision and Pattern Recognition (2019)","DOI":"10.1109\/CVPR.2019.01298"},{"key":"9736_CR23","doi-asserted-by":"crossref","unstructured":"Yang, Z. T., Sun, Y., Liu, S., Shen, X.Y., Jia, J .Y. : STD: Sparse-to-Dense 3D Object Detector for Point Cloud. The IEEE\/CVF International Conference on Computer Vision. 1951\u20131960 (2019)","DOI":"10.1109\/ICCV.2019.00204"},{"key":"9736_CR24","unstructured":"Ioffe, S., Szegedy, C. ; Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift. 1502. 03167 (2015)"},{"key":"9736_CR25","doi-asserted-by":"crossref","unstructured":"Law, H., Deng, J.: CornerNet: Detecting Objects as Paired Keypoints. European conference on computer vision. 765\u2013781 (2018)","DOI":"10.1007\/978-3-030-01264-9_45"},{"key":"9736_CR26","doi-asserted-by":"crossref","unstructured":"Ku, J., Mozififian, M., Lee, J., Harakeh, A., Waslander, S.L.: Joint 3d proposal generation and target detection from view aggregation. IEEE\/RSJ International Conference on Intelligent Robots and Systems. 1\u20138 (2018).","DOI":"10.1109\/IROS.2018.8594049"},{"key":"9736_CR27","doi-asserted-by":"crossref","unstructured":"Charles, R. Q., Liu, W., Wu, C. X., Su, H., Guibas, L. J. : Frustum PointNets for 3D target detection From RGB-D Data. The IEEE Conference on Computer Vision and Pattern Recognition. 918\u2013927 (2018)","DOI":"10.1109\/CVPR.2018.00102"},{"key":"9736_CR28","doi-asserted-by":"crossref","unstructured":"Wang, Z., Ding, S. H., Li, Y., Zhao, M.M., Roychowdhury, S., Wallin, A., Sapiro, G., Qiu, Q.: \u201cRange Adaptation for 3D target detection in LiDAR. The IEEE\/CVF International Conference on Computer Vision. (2019)","DOI":"10.1109\/ICCVW.2019.00285"},{"key":"9736_CR29","doi-asserted-by":"crossref","unstructured":"Shi, S. S., Wang, X. G., Li, H. S.: PointRCNN: 3D Object Proposal Generation and Detection From Point Cloud. The IEEE CVF Conference on Computer Vision and Pattern Recognition. (2019)","DOI":"10.1109\/CVPR.2019.00086"}],"container-title":["Journal of Grid Computing"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s10723-023-09736-0.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1007\/s10723-023-09736-0\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s10723-023-09736-0.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,11,8]],"date-time":"2024-11-08T15:28:47Z","timestamp":1731079727000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/s10723-023-09736-0"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2024,1,19]]},"references-count":29,"journal-issue":{"issue":"1","published-print":{"date-parts":[[2024,3]]}},"alternative-id":["9736"],"URL":"https:\/\/doi.org\/10.1007\/s10723-023-09736-0","relation":{},"ISSN":["1570-7873","1572-9184"],"issn-type":[{"type":"print","value":"1570-7873"},{"type":"electronic","value":"1572-9184"}],"subject":[],"published":{"date-parts":[[2024,1,19]]},"assertion":[{"value":"24 July 2023","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"30 December 2023","order":2,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"19 January 2024","order":3,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}},{"order":1,"name":"Ethics","group":{"name":"EthicsHeading","label":"Declarations"}},{"value":"The authors declare no competing interests.","order":2,"name":"Ethics","group":{"name":"EthicsHeading","label":"Competing Interests"}}],"article-number":"14"}}