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Efficient Vehicle Segmentation and Classification in Urban Point Clouds Using Modified Euclidean Clustering

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Bibliographic Details
Published in:Applied Computational Intelligence and Soft Computing
Format: Online Article RSS Article
Published: 2026
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container_title Applied Computational Intelligence and Soft Computing
description
discipline_display Natural Sciences
discipline_facet Natural Sciences
format Online Article
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genre Journal Article
id rss_article:44813
institution FRELIP
journal_source_facet Applied Computational Intelligence and Soft Computing
publishDate 2026
publishDateSort 2026
record_format rss_article
spellingShingle Efficient Vehicle Segmentation and Classification in Urban Point Clouds Using Modified Euclidean Clustering
Mathematics
Natural Sciences — Mathematical Sciences
Natural Sciences
sub_discipline_display Natural Sciences — Mathematical Sciences
sub_discipline_facet Natural Sciences — Mathematical Sciences
subject_display Mathematics
Natural Sciences — Mathematical Sciences
Natural Sciences
Mathematics
Natural Sciences — Mathematical Sciences
Natural Sciences
subject_facet Mathematics
Natural Sciences — Mathematical Sciences
Natural Sciences
title Efficient Vehicle Segmentation and Classification in Urban Point Clouds Using Modified Euclidean Clustering
title_auth Efficient Vehicle Segmentation and Classification in Urban Point Clouds Using Modified Euclidean Clustering
title_full Efficient Vehicle Segmentation and Classification in Urban Point Clouds Using Modified Euclidean Clustering
title_fullStr Efficient Vehicle Segmentation and Classification in Urban Point Clouds Using Modified Euclidean Clustering
title_full_unstemmed Efficient Vehicle Segmentation and Classification in Urban Point Clouds Using Modified Euclidean Clustering
title_short Efficient Vehicle Segmentation and Classification in Urban Point Clouds Using Modified Euclidean Clustering
title_sort efficient vehicle segmentation and classification in urban point clouds using modified euclidean clustering
topic Mathematics
Natural Sciences — Mathematical Sciences
Natural Sciences
url https://www.hindawi.com/journals/acisc/2026/8264954/