{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,25]],"date-time":"2026-06-25T05:33:26Z","timestamp":1782365606068,"version":"3.54.5"},"reference-count":33,"publisher":"MDPI AG","issue":"20","license":[{"start":{"date-parts":[[2022,10,14]],"date-time":"2022-10-14T00:00:00Z","timestamp":1665705600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"Open Fund of the Key Laboratory of Degraded and Unused Land Consolidation Engineering, Ministry of Natural Resources","award":["SXDJ2019-4"],"award-info":[{"award-number":["SXDJ2019-4"]}]},{"name":"Open Fund of the Key Laboratory of Degraded and Unused Land Consolidation Engineering, Ministry of Natural Resources","award":["H7P210062"],"award-info":[{"award-number":["H7P210062"]}]},{"name":"Open Fund of the Key Laboratory of Degraded and Unused Land Consolidation Engineering, Ministry of Natural Resources","award":["51874306"],"award-info":[{"award-number":["51874306"]}]},{"name":"Scientific Re-search Project of Nanjing Institute of Surveying, Mapping &amp; Geographical Investigation, CO. Ltd.","award":["SXDJ2019-4"],"award-info":[{"award-number":["SXDJ2019-4"]}]},{"name":"Scientific Re-search Project of Nanjing Institute of Surveying, Mapping &amp; Geographical Investigation, CO. Ltd.","award":["H7P210062"],"award-info":[{"award-number":["H7P210062"]}]},{"name":"Scientific Re-search Project of Nanjing Institute of Surveying, Mapping &amp; Geographical Investigation, CO. Ltd.","award":["51874306"],"award-info":[{"award-number":["51874306"]}]},{"name":"Natural Science Foundation of China","award":["SXDJ2019-4"],"award-info":[{"award-number":["SXDJ2019-4"]}]},{"name":"Natural Science Foundation of China","award":["H7P210062"],"award-info":[{"award-number":["H7P210062"]}]},{"name":"Natural Science Foundation of China","award":["51874306"],"award-info":[{"award-number":["51874306"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>With the rapid development of cities, semantic segmentation of urban scenes, as an important and effective imaging method, can accurately obtain the distribution information of typical urban ground features, reflecting the development scale and the level of greenery in the cities. There are some challenging problems in the semantic segmentation of point clouds in urban scenes, including different scales, imbalanced class distribution, and missing data caused by occlusion. Based on the point cloud semantic segmentation network RandLA-Net, we propose the semantic segmentation networks RandLA-Net++ and RandLA-Net3+. The RandLA-Net++ network is a deep fusion of the shallow and deep features of the point clouds, and a series of nested dense skip connections is used between the encoder and decoder. RandLA-Net3+ is based on the multi-scale connection between the encoder and decoder; it also connects internally within the decoder to capture fine-grained details and coarse-grained semantic information at a full scale. We also propose incorporating dilated convolution to increase the receptive field and compare the improvement effect of different loss functions on sample class imbalance. After verification and analysis of our labeled urban scene LiDAR point cloud dataset\u2014called NJSeg-3D\u2014the mIoU of the RandLA-Net++ and RandLA-Net3+ networks is 3.4% and 3.2% higher, respectively, than the benchmark network RandLA-Net.<\/jats:p>","DOI":"10.3390\/rs14205134","type":"journal-article","created":{"date-parts":[[2022,10,17]],"date-time":"2022-10-17T03:43:58Z","timestamp":1665978238000},"page":"5134","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":22,"title":["Multi-Feature Aggregation for Semantic Segmentation of an Urban Scene Point Cloud"],"prefix":"10.3390","volume":"14","author":[{"given":"Jiaqing","family":"Chen","sequence":"first","affiliation":[{"name":"Key Laboratory of Degraded and Unused Land Consolidation Engineering, Ministry of Natural Resources, Xi\u2019an 710075, China"},{"name":"School of Environment and Spatial Informatics, China University of Mining and Technology, Xuzhou 221116, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yindi","family":"Zhao","sequence":"additional","affiliation":[{"name":"Key Laboratory of Degraded and Unused Land Consolidation Engineering, Ministry of Natural Resources, Xi\u2019an 710075, China"},{"name":"School of Environment and Spatial Informatics, China University of Mining and Technology, Xuzhou 221116, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Congtang","family":"Meng","sequence":"additional","affiliation":[{"name":"School of Environment and Spatial Informatics, China University of Mining and Technology, Xuzhou 221116, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yang","family":"Liu","sequence":"additional","affiliation":[{"name":"School of Environment and Spatial Informatics, China University of Mining and Technology, Xuzhou 221116, China"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2022,10,14]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","unstructured":"Kasznar, A.P.P., Hammad, A.W., Najjar, M., Linhares Qualharini, E., Figueiredo, K., Soares, C.A.P., and Haddad, A.N. 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