{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,11]],"date-time":"2026-03-11T11:49:39Z","timestamp":1773229779952,"version":"3.50.1"},"reference-count":34,"publisher":"Springer Science and Business Media LLC","issue":"2","license":[{"start":{"date-parts":[[2026,1,19]],"date-time":"2026-01-19T00:00:00Z","timestamp":1768780800000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by-nc-nd\/4.0"},{"start":{"date-parts":[[2026,2,25]],"date-time":"2026-02-25T00:00:00Z","timestamp":1771977600000},"content-version":"vor","delay-in-days":37,"URL":"https:\/\/creativecommons.org\/licenses\/by-nc-nd\/4.0"}],"funder":[{"name":"Ningxia Natural Science Foundation General Project","award":["2023AAC03889"],"award-info":[{"award-number":["2023AAC03889"]}]},{"name":"National Key Research and Development Program of China","award":["2023YFC3011704-2"],"award-info":[{"award-number":["2023YFC3011704-2"]}]}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["J. King Saud Univ. Comput. Inf. Sci."],"published-print":{"date-parts":[[2026,3]]},"DOI":"10.1007\/s44443-025-00451-2","type":"journal-article","created":{"date-parts":[[2026,1,19]],"date-time":"2026-01-19T22:24:18Z","timestamp":1768861458000},"update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["HBD-NanoDetPlus:a lightweight detection model for vehicle high beam headlights in rainy and snowy weather"],"prefix":"10.1007","volume":"38","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-1980-1858","authenticated-orcid":false,"given":"Lili","family":"Zhang","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Ke","family":"Zhang","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Wenshuo","family":"Han","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Long","family":"Zhang","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Ruiyang","family":"Xiao","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Wei","family":"Wei","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jing","family":"Li","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Hongxin","family":"Tan","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Pei","family":"Yu","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2026,1,19]]},"reference":[{"issue":"2","key":"451_CR1","doi-asserted-by":"publisher","first-page":"522","DOI":"10.3390\/s24020522","volume":"24","author":"I Ashraf","year":"2024","unstructured":"Ashraf I, Hur S, Kim G et al (2024) Analyzing performance of YOLOx for detecting vehicles in bad weather conditions. Sensors 24(2):522","journal-title":"Sensors"},{"key":"451_CR2","doi-asserted-by":"crossref","unstructured":"Chen LC, Papandreou G, Kokkinos I et al (2017) Deeplab: Semantic image segmentation with deep convolutional nets, atrous convolution, and fully connected CRFs. IEEE Transactions on Pattern Analysis and Machine Intelligence 40(4):834\u2013848. https:\/\/ieeexplore.ieee.org\/abstract\/document\/7913730.","DOI":"10.1109\/TPAMI.2017.2699184"},{"key":"451_CR3","doi-asserted-by":"publisher","unstructured":"Chen XY, Ge MM, Yao ZT et al (2023) LiDAR filtering algorithm under rain and snow weather. Journal of Instruments and Meters. 44(7):172\u2013181. https:\/\/doi.org\/10.19650\/j.cnki.cjsi.J2311227.","DOI":"10.19650\/j.cnki.cjsi.J2311227"},{"key":"451_CR4","doi-asserted-by":"crossref","unstructured":"Dai XY, Chen YP, Yang JW et al (2021) Dynamic DETR: End-to-end object detection with dynamic attention. In Proceedings of the IEEE\/CVF International Conference on Computer Vision, pp 2988\u20132997. https:\/\/openaccess.thecvf.com\/content\/ICCV2021\/html\/Dai_Dynamic_DETR_End-to-End_Object_Detection_With_Dynamic_Attention_ICCV_2021_paper.html?ref=https:\/\/githubhelp.com.","DOI":"10.1109\/ICCV48922.2021.00298"},{"key":"451_CR5","unstructured":"Ge Z, Liu ST, Wang F et al (2021) YOLOX: Exceeding YOLO series in 2021. arXiv preprint arXiv:2107.08430. https:\/\/arxiv.org\/abs\/2107.08430."},{"key":"451_CR6","doi-asserted-by":"crossref","unstructured":"Girshick R (2015) Fast R-CNN. In Proceedings of the IEEE International Conference on Computer Vision, pp 1440\u20131448. https:\/\/openaccess.thecvf.com\/content_iccv_2015\/html\/Girshick_Fast_R-CNN_ICCV_2015_paper.html.","DOI":"10.1109\/ICCV.2015.169"},{"issue":"12","key":"451_CR7","first-page":"256","volume":"48","author":"H Gong","year":"2021","unstructured":"Gong H, Liu PS (2021) Detection method of high beam of vehicles driving at night. Computer Science 48(12):256\u2013263","journal-title":"Computer Science"},{"key":"451_CR8","doi-asserted-by":"crossref","unstructured":"Hou QB, Zhou DQ, Feng JS (2021) Coordinate attention for efficient mobile network design. In Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, pp 13713\u201313722. https:\/\/openaccess.thecvf.com\/content\/CVPR2021\/html\/Hou_Coordinate_Attention_for_Efficient_Mobile_Network_Design_CVPR_2021_paper.html.","DOI":"10.1109\/CVPR46437.2021.01350"},{"key":"451_CR9","doi-asserted-by":"crossref","unstructured":"Hu J, Shen L, Sun G (2018) Squeeze-and-excitation networks. In Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, pp 7132\u20137141. https:\/\/openaccess.thecvf.com\/content_cvpr_2018\/html\/Hu_Squeeze-and-Excitation_Networks_CVPR_2018_paper.html.","DOI":"10.1109\/CVPR.2018.00745"},{"key":"451_CR10","unstructured":"Jocher G, Stoken A, Borovec J et al (2020) ultralytics\/yolov5: v3.0. Zenodo. https:\/\/ui.adsabs.harvard.edu\/abs\/2020zndo...3983579J\/abstract."},{"key":"451_CR11","unstructured":"Kenk MA, Mahmoud H (2020) DAWN: Vehicle detection in adverse weather nature data set. arXiv preprint arXiv:2008.05402. https:\/\/arxiv.org\/abs\/2008.05402."},{"issue":"1","key":"451_CR12","doi-asserted-by":"publisher","DOI":"10.3390\/app13010219","volume":"13","author":"E Khatab","year":"2022","unstructured":"Khatab E, Onsy A, Varley M et al (2022) A lightweight network for real-time rain streaks and rain accumulation removal from single images captured by AVS. Appl Sci 13(1):219","journal-title":"Appl Sci"},{"issue":"03","key":"451_CR13","first-page":"166","volume":"32","author":"C Li","year":"2021","unstructured":"Li C, Kang JX, Zeng DB (2021) Research and implementation of a new method for calibrating high beam intensity of automobiles based on computer vision. J Illum Eng 32(03):166\u2013171","journal-title":"J Illum Eng"},{"key":"451_CR14","doi-asserted-by":"publisher","unstructured":"Li B (2023) Road detection method under different weather conditions. Dalian University of Technology. https:\/\/doi.org\/10.26991\/d.cnki.gdllu.2023.000799.","DOI":"10.26991\/d.cnki.gdllu.2023.000799"},{"issue":"16","key":"451_CR15","doi-asserted-by":"publisher","first-page":"16276","DOI":"10.1109\/JSEN.2022.3188985","volume":"22","author":"J Lin","year":"2022","unstructured":"Lin J, Yin HL, Yan J et al (2022) Improved 3d object detector under snowfall weather condition based on LiDAR point cloud. IEEE Sens J 22(16):16276\u201316292","journal-title":"IEEE Sens J"},{"key":"451_CR16","first-page":"158","volume":"17","author":"YJ Liu","year":"2024","unstructured":"Liu YJ (2024) Research on a new method for calibrating high beam intensity of automobiles based on computer vision. Automobile Test Report 17:158\u2013160","journal-title":"Automobile Test Report"},{"key":"451_CR17","doi-asserted-by":"publisher","unstructured":"Pan XJ (2015) Research on the automatic capture system for illegal use of high beams. Xi\u2019an University of Technology. https:\/\/doi.org\/10.27398\/d.cnki.gxalu.2015.000082.","DOI":"10.27398\/d.cnki.gxalu.2015.000082"},{"key":"451_CR18","doi-asserted-by":"crossref","unstructured":"Qin Z, Li ZM, Zhang ZN et al (2019) ThunderNet: Towards real-time generic object detection on mobile devices. In Proceedings of the IEEE\/CVF International Conference on Computer Vision, pp 6718\u20136727. https:\/\/openaccess.thecvf.com\/content_ICCV_2019\/html\/Qin_ThunderNet_Towards_Real-Time_Generic_Object_Detection_on_Mobile_Devices_ICCV_2019_paper.html.","DOI":"10.1109\/ICCV.2019.00682"},{"key":"451_CR19","doi-asserted-by":"crossref","unstructured":"Sakaridis C, Dai DX, Van Gool L (2021) ACDC: The adverse conditions data set with correspondences for semantic driving scene understanding. In Proceedings of the IEEE\/CVF International Conference on Computer Vision, pp 10765\u201310775. https:\/\/openaccess.thecvf.com\/content\/ICCV2021\/html\/Sakaridis_ACDC_The_Adverse_Conditions_Data set_With_Correspondences_for_Semantic_Driving_ICCV_2021_paper.html.","DOI":"10.1109\/ICCV48922.2021.01059"},{"key":"451_CR20","doi-asserted-by":"publisher","unstructured":"Sohan M, Thotakura SR, Reddy CVR (2024) A review on YOLOv8 and its advancements. In International Conference on Data Intelligence and Cognitive Informatics. Springer, Singapore, pp 529\u2013545. https:\/\/link.springer.com\/chapter\/https:\/\/doi.org\/10.1007\/978-981-99-7962-2_39.","DOI":"10.1007\/978-981-99-7962-2_39"},{"key":"451_CR21","doi-asserted-by":"publisher","unstructured":"Sun H (2021) Nighttime high beam detection integrating multi-target tracking and evidence chain forensics. Shanghai University of Engineering Science. https:\/\/doi.org\/10.27715\/d.cnki.gshgj.2021.000188.","DOI":"10.27715\/d.cnki.gshgj.2021.000188"},{"key":"451_CR22","doi-asserted-by":"crossref","unstructured":"Szegedy C, Ioffe S, Vanhoucke V et al (2017) Inception-v4, inception-resnet and the impact of residual connections on learning. In Proceedings of the AAAI Conference on Artificial Intelligence 31(1). https:\/\/ojs.aaai.org\/index.php\/aaai\/article\/view\/11231.","DOI":"10.1609\/aaai.v31i1.11231"},{"key":"451_CR23","doi-asserted-by":"crossref","unstructured":"Tan MX, Pang RM, Le QV (2020) EfficientDet: Scalable and efficient object detection. In Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, pp 10781\u201310790. https:\/\/openaccess.thecvf.com\/content_CVPR_2020\/html\/Tan_EfficientDet_Scalable_and_Efficient_Object_Detection_CVPR_2020_paper.html.","DOI":"10.1109\/CVPR42600.2020.01079"},{"key":"451_CR24","unstructured":"Tian YJ, Ye QX, David D (2025) YOLOv12: Attention-centric real-time object detectors. arXiv preprint arXiv:2502.12524. https:\/\/arxiv.org\/abs\/2502.12524."},{"key":"451_CR25","doi-asserted-by":"crossref","unstructured":"Wang YH, Wu YF (2024) A real-time detection algorithm based on improved NanoDet for shaft parts. In 2024 16th International Conference on Intelligent Human-Machine Systems and Cybernetics (IHMSC) IEEE, pp 174\u2013178. https:\/\/ieeexplore.ieee.org\/abstract\/document\/10731505.","DOI":"10.1109\/IHMSC62065.2024.00047"},{"key":"451_CR26","doi-asserted-by":"crossref","unstructured":"Wang QL, Wu BG, Zhu PF et al (2020) ECA-Net: Efficient channel attention for deep convolutional neural networks. In Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, pp 11534\u201311542.https:\/\/openaccess.thecvf.com\/content_CVPR_2020\/html\/Wang_ECA-Net_Efficient_Channel_Attention_for_Deep_Convolutional_Neural_Networks_CVPR_2020_paper.html.","DOI":"10.1109\/CVPR42600.2020.01155"},{"key":"451_CR27","doi-asserted-by":"crossref","unstructured":"Wang A, Chen H, Liu LH et al (2024) YOLOv10: Real-time end-to-end object detection. Advances in Neural Information Processing Systems 37:107984\u2013108011. https:\/\/proceedings.neurips.cc\/paper_files\/paper\/2024\/hash\/c34ddd05eb089991f06f3c5dc36836e0-Abstract-Conference.html.","DOI":"10.52202\/079017-3429"},{"key":"451_CR28","doi-asserted-by":"crossref","unstructured":"Woo S, Park J, Lee JY et al (2018) CBAM: Convolutional block attention module. In Proceedings of the European Conference on Computer Vision (ECCV), pp 3\u201319. https:\/\/openaccess.thecvf.com\/content_ECCV_2018\/html\/Sanghyun_Woo_Convolutional_Block_Attention_ECCV_2018_paper.html.","DOI":"10.1007\/978-3-030-01234-2_1"},{"key":"451_CR29","first-page":"78","volume":"1","author":"YQ Wu","year":"2018","unstructured":"Wu YQ, Hua JF, Chen Y et al (2018) Difficulties and counter-measures for illegal use of driving beam headlamp of motor vehicles. China Public Security 1:78\u201381","journal-title":"China Public Security"},{"issue":"5","key":"451_CR30","doi-asserted-by":"publisher","first-page":"8950","DOI":"10.1109\/JSEN.2024.3505234","volume":"25","author":"XY Yan","year":"2025","unstructured":"Yan XY, Yang JX, Liang Y et al (2025) AdverseNet: a LiDAR point cloud denoising network for autonomous driving in rainy, snowy, and foggy weather. IEEE Sens J 25(5):8950\u20138961","journal-title":"IEEE Sens J"},{"issue":"24","key":"451_CR31","first-page":"351","volume":"57","author":"GL Yang","year":"2020","unstructured":"Yang GL, Yu DL, Wang Y et al (2020) Moving target detection under rain and snow weather conditions. Laser & Optoelectronics Progress 57(24):351\u2013358","journal-title":"Laser & Optoelectronics Progress"},{"issue":"1","key":"451_CR32","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1007\/s11227-024-06809-z","volume":"81","author":"LL Zhang","year":"2025","unstructured":"Zhang LL, Zhang K, Yang K et al (2025) Driving risks from light pollution: an improved YOLOv8 detection network for high beam vehicle image recognition. The Journal of Supercomputing 81(1):1\u201323","journal-title":"The Journal of Supercomputing"},{"issue":"05","key":"451_CR33","first-page":"659","volume":"46","author":"LL Zhang","year":"2025","unstructured":"Zhang LL, Zhang K, Yang K et al (2025) Research on YOLOv10-ECC algorithm for vehicle high beam detection in traffic law enforcement. Acta Metrologica Sinica 46(05):659\u2013666","journal-title":"Acta Metrologica Sinica"},{"key":"451_CR34","doi-asserted-by":"publisher","unstructured":"Zhao Y (2023) Design and implementation of a pedestrian detection method under rain and snow weather. Beijing University of Posts and Telecommunications. https:\/\/doi.org\/10.26969\/d.cnki.gbydu.2023.000633.","DOI":"10.26969\/d.cnki.gbydu.2023.000633"}],"container-title":["Journal of King Saud University Computer and Information Sciences"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/article\/10.1007\/s44443-025-00451-2","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s44443-025-00451-2.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s44443-025-00451-2.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,3,10]],"date-time":"2026-03-10T14:40:10Z","timestamp":1773153610000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/s44443-025-00451-2"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026,1,19]]},"references-count":34,"journal-issue":{"issue":"2","published-print":{"date-parts":[[2026,3]]}},"alternative-id":["451"],"URL":"https:\/\/doi.org\/10.1007\/s44443-025-00451-2","relation":{},"ISSN":["1319-1578","2213-1248"],"issn-type":[{"value":"1319-1578","type":"print"},{"value":"2213-1248","type":"electronic"}],"subject":[],"published":{"date-parts":[[2026,1,19]]},"assertion":[{"value":"4 September 2025","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"24 December 2025","order":2,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"19 January 2026","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 all authors declare no conflict of interest.","order":2,"name":"Ethics","group":{"name":"EthicsHeading","label":"Conflict of interest"}}],"article-number":"74"}}