{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,1,6]],"date-time":"2026-01-06T05:52:45Z","timestamp":1767678765109,"version":"3.48.0"},"reference-count":30,"publisher":"Institute of Electrical and Electronics Engineers (IEEE)","license":[{"start":{"date-parts":[[2026,1,1]],"date-time":"2026-01-01T00:00:00Z","timestamp":1767225600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/legalcode"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IEEE Access"],"published-print":{"date-parts":[[2026]]},"DOI":"10.1109\/access.2025.3649252","type":"journal-article","created":{"date-parts":[[2025,12,29]],"date-time":"2025-12-29T18:39:29Z","timestamp":1767033569000},"page":"549-561","source":"Crossref","is-referenced-by-count":0,"title":["Segmentation of Power Tower Point Clouds With Color-Guided Perception and Self-Supervised Pretraining"],"prefix":"10.1109","volume":"14","author":[{"ORCID":"https:\/\/orcid.org\/0009-0004-1179-2514","authenticated-orcid":false,"given":"Wei","family":"Liu","sequence":"first","affiliation":[{"name":"Hubei Central China Technology Development of Electric Power Company Ltd., Wuhan, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0009-0001-2349-6702","authenticated-orcid":false,"given":"Yang","family":"Jin","sequence":"additional","affiliation":[{"name":"State Grid Hubei Electric Power Research Institute, Wuhan, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Meng","family":"Jiang","sequence":"additional","affiliation":[{"name":"Hubei Central China Technology Development of Electric Power Company Ltd., Wuhan, China"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"263","reference":[{"key":"ref1","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2017.16"},{"key":"ref2","first-page":"1","article-title":"PointNet++: Deep hierarchical feature learning on point sets in a metric space","volume-title":"Proc. Adv. Neural Inf. Process. Syst.","volume":"30","author":"Qi"},{"key":"ref3","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-58580-8_34"},{"key":"ref4","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR52688.2022.01871"},{"key":"ref5","doi-asserted-by":"publisher","DOI":"10.1142\/S2811032324400010"},{"key":"ref6","doi-asserted-by":"publisher","DOI":"10.1109\/WACV57701.2024.00335"},{"key":"ref7","first-page":"28223","article-title":"Contrast with reconstruct: Contrastive 3D representation learning guided by generative pretraining","volume-title":"Proc. Int. Conf. Mach. Learn.","author":"Qi"},{"key":"ref8","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR52734.2025.00131"},{"key":"ref9","article-title":"Masked clustering prediction for unsupervised point cloud pre-training","author":"Ren","year":"2025","journal-title":"arXiv:2508.08910"},{"key":"ref10","article-title":"Attention-guided multi-scale local reconstruction for point clouds via masked autoencoder self-supervised learning","author":"Cao","year":"2025","journal-title":"arXiv:2507.04084"},{"key":"ref11","doi-asserted-by":"publisher","DOI":"10.1016\/j.eswa.2023.121354"},{"key":"ref12","doi-asserted-by":"publisher","DOI":"10.1177\/17298806221098506"},{"key":"ref13","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR52734.2025.00133"},{"key":"ref14","doi-asserted-by":"publisher","DOI":"10.3390\/s24051458"},{"key":"ref15","doi-asserted-by":"publisher","DOI":"10.1186\/s13007-023-01099-7"},{"key":"ref16","doi-asserted-by":"publisher","DOI":"10.1016\/j.autcon.2025.105963"},{"key":"ref17","doi-asserted-by":"publisher","DOI":"10.1145\/3664647.3681301"},{"key":"ref18","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR52729.2023.01302"},{"key":"ref19","doi-asserted-by":"publisher","DOI":"10.3390\/s23198338"},{"key":"ref20","doi-asserted-by":"publisher","DOI":"10.1063\/5.0189991"},{"key":"ref21","doi-asserted-by":"publisher","DOI":"10.1007\/s00530-024-01389-7"},{"key":"ref22","doi-asserted-by":"publisher","DOI":"10.1016\/j.image.2023.117004"},{"key":"ref23","doi-asserted-by":"publisher","DOI":"10.1109\/TGRS.2025.3535800"},{"key":"ref24","doi-asserted-by":"publisher","DOI":"10.3390\/s25082474"},{"key":"ref25","doi-asserted-by":"publisher","DOI":"10.1371\/journal.pone.0329146"},{"key":"ref26","doi-asserted-by":"publisher","DOI":"10.1038\/s41598-025-99240-0"},{"key":"ref27","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2019.00651"},{"key":"ref28","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR42600.2020.01112"},{"key":"ref29","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV48922.2021.01595"},{"key":"ref30","first-page":"23192","article-title":"PointNeXt: Revisiting PointNet++ with improved training and scaling strategies","volume-title":"Proc. Adv. Neural Inf. Process. Syst.","volume":"35","author":"Qian"}],"container-title":["IEEE Access"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx8\/6287639\/11323511\/11317953.pdf?arnumber=11317953","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,1,6]],"date-time":"2026-01-06T05:49:02Z","timestamp":1767678542000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/11317953\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026]]},"references-count":30,"URL":"https:\/\/doi.org\/10.1109\/access.2025.3649252","relation":{},"ISSN":["2169-3536"],"issn-type":[{"type":"electronic","value":"2169-3536"}],"subject":[],"published":{"date-parts":[[2026]]}}}