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Moreover, the Scylla-Intersection over Union loss function is introduced to comprehensively evaluate bounding box similarity, thereby improving object detection accuracy. Ablation experiments conducted on a modified Pascal Visual Object Classes (Pascal VOC) dataset demonstrate that LW-DETR, while maintaining acceptable detection accuracy, achieves a 135.3% increase in frames per second, a 71.7% reduction in parameters, and a 73.7% decrease in computational load, leading to effective lightweight performance. Comparative experiments with other popular object detection algorithms further confirm that LW-DETR significantly enhances detection speed while maintaining high accuracy, considerably reducing model size and validating the effectiveness of these improvements.<\/jats:p>","DOI":"10.1007\/s40747-025-02111-4","type":"journal-article","created":{"date-parts":[[2025,10,24]],"date-time":"2025-10-24T08:32:56Z","timestamp":1761294776000},"update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":2,"title":["LW-DETR: a lightweight transformer-based object detection algorithm for efficient railway crossing surveillance"],"prefix":"10.1007","volume":"11","author":[{"given":"Baoye","family":"Song","sequence":"first","affiliation":[]},{"given":"Shihao","family":"Zhao","sequence":"additional","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0002-9576-7401","authenticated-orcid":false,"given":"Zidong","family":"Wang","sequence":"additional","affiliation":[]},{"given":"Jianyu","family":"Chen","sequence":"additional","affiliation":[]},{"given":"Weibo","family":"Liu","sequence":"additional","affiliation":[]},{"given":"Xiaohui","family":"Liu","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2025,10,24]]},"reference":[{"issue":"10","key":"2111_CR1","doi-asserted-by":"publisher","first-page":"2023","DOI":"10.1080\/00207721.2024.2328781","volume":"55","author":"R Caballero-\u00c1guila","year":"2024","unstructured":"Caballero-\u00c1guila R, Hu J, Linares-P\u00e9rez J (2024) Filtering and smoothing estimation algorithms from uncertain nonlinear observations with time-correlated additive noise and random deception attacks. 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