{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,1,29]],"date-time":"2025-01-29T05:48:29Z","timestamp":1738129709071,"version":"3.33.0"},"reference-count":36,"publisher":"Springer Science and Business Media LLC","issue":"1","license":[{"start":{"date-parts":[[2024,12,5]],"date-time":"2024-12-05T00:00:00Z","timestamp":1733356800000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2024,12,5]],"date-time":"2024-12-05T00:00:00Z","timestamp":1733356800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"}],"funder":[{"name":"the National Key Research and Development Program of China under Grant","award":["2023YFC3008904"],"award-info":[{"award-number":["2023YFC3008904"]}]},{"name":"the Fundamental Research Funds for Beijing University of Civil Engineering and Architecture under Grant","award":["X20109"],"award-info":[{"award-number":["X20109"]}]}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["SIViP"],"published-print":{"date-parts":[[2025,1]]},"DOI":"10.1007\/s11760-024-03735-8","type":"journal-article","created":{"date-parts":[[2024,12,5]],"date-time":"2024-12-05T05:10:35Z","timestamp":1733375435000},"update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["YOLOv5s-FAC: enhanced feature association detector for person-vehicle counting in smart park"],"prefix":"10.1007","volume":"19","author":[{"given":"WeiGuang","family":"Zou","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"YuLing","family":"Hu","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"XinYi","family":"Wang","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"JiaFeng","family":"Li","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2024,12,5]]},"reference":[{"key":"3735_CR1","unstructured":"Software and Integrated Circuits: 2022 China Smart Park Development Research Report. (2022)"},{"key":"3735_CR2","doi-asserted-by":"publisher","first-page":"6827","DOI":"10.1007\/s11042-018-6394-6","volume":"78","author":"MR Lee","year":"2019","unstructured":"Lee, M.R., Lin, D.T.: Vehicle counting based on a stereo vision depth maps for parking management. Multimed. Tools Appl. 78, 6827\u20136846 (2019). https:\/\/doi.org\/10.1007\/s11042-018-6394-6","journal-title":"Multimed. Tools Appl."},{"key":"3735_CR3","doi-asserted-by":"publisher","first-page":"108362","DOI":"10.1016\/j.cie.2022.108362","volume":"171","author":"TY Chang","year":"2022","unstructured":"Chang, T.Y., Ku, C.C.Y., Cheng, T.Y., Chung, C.K., Chang Sanchez, E.: Modular counting management system for mall parking services. Comput. Ind. Eng. 171, 108362 (2022). https:\/\/doi.org\/10.1016\/j.cie.2022.108362","journal-title":"Comput. Ind. Eng."},{"key":"3735_CR4","doi-asserted-by":"publisher","first-page":"1938","DOI":"10.1007\/s11263-022-01626-4","volume":"130","author":"Q Zhang","year":"2022","unstructured":"Zhang, Q., Chan, A.B.: Wide-area crowd counting: multi-view fusion networks for counting in large scenes. Int. J. Comput. Vis. 130, 1938\u20131960 (2022). https:\/\/doi.org\/10.1007\/s11263-022-01626-4","journal-title":"Int. J. Comput. Vis."},{"key":"3735_CR5","doi-asserted-by":"publisher","first-page":"1099","DOI":"10.1007\/s10586-022-03749-2","volume":"26","author":"W Zhai","year":"2023","unstructured":"Zhai, W., Gao, M., Souri, A., Li, Q., Guo, X., Shang, J., Zou, G.: An attentive hierarchy ConvNet for crowd counting in smart city. Clust. Comput. 26, 1099\u20131111 (2023). https:\/\/doi.org\/10.1007\/s10586-022-03749-2","journal-title":"Clust. Comput."},{"key":"3735_CR6","doi-asserted-by":"publisher","first-page":"328","DOI":"10.1016\/j.future.2023.05.013","volume":"147","author":"X Guo","year":"2023","unstructured":"Guo, X., Song, K., Gao, M., Zhai, W., Li, Q., Jeon, G.: Crowd counting in smart city via lightweight ghost attention pyramid network. Future Gener. Comput. Syst. 147, 328\u2013338 (2023). https:\/\/doi.org\/10.1016\/j.future.2023.05.013","journal-title":"Future Gener. Comput. Syst."},{"key":"3735_CR7","doi-asserted-by":"publisher","first-page":"15920","DOI":"10.1109\/tits.2023.3296571","volume":"24","author":"X Guo","year":"2023","unstructured":"Guo, X., Gao, M., Zhai, W., Li, Q., Jeon, G.: Scale region recognition network for object counting in intelligent transportation system. IEEE Trans. Intell. Transp. Syst. 24, 15920\u201315929 (2023). https:\/\/doi.org\/10.1109\/tits.2023.3296571","journal-title":"IEEE Trans. Intell. Transp. Syst."},{"key":"3735_CR8","doi-asserted-by":"publisher","first-page":"18930","DOI":"10.1109\/jiot.2023.3268226","volume":"10","author":"W Zhai","year":"2023","unstructured":"Zhai, W., Gao, M., Guo, X., Li, Q., Jeon, G.: Scale-context perceptive network for crowd counting and localization in smart city system. IEEE Internet Things J. 10, 18930\u201318940 (2023). https:\/\/doi.org\/10.1109\/jiot.2023.3268226","journal-title":"IEEE Internet Things J."},{"key":"3735_CR9","doi-asserted-by":"publisher","first-page":"359","DOI":"10.1007\/s11036-023-02090-1","volume":"28","author":"X Guo","year":"2023","unstructured":"Guo, X., Gao, M., Zhai, W., Li, Q., Kim, K.H., Jeon, G.: Dense attention fusion network for object counting in IoT system. Mob. Netw. Appl. 28, 359\u2013368 (2023). https:\/\/doi.org\/10.1007\/s11036-023-02090-1","journal-title":"Mob. Netw. Appl."},{"key":"3735_CR10","doi-asserted-by":"publisher","first-page":"255","DOI":"10.1109\/tetci.2023.3300172","volume":"8","author":"MH Yen","year":"2024","unstructured":"Yen, M.H., Lin, B.S., Kuo, Y.L., Lee, I.J., Lin, B.S.: Adaptive indoor people-counting system based on edge AI computing. IEEE Trans. Emerg. Top. Comput. Intell. 8, 255\u2013263 (2024). https:\/\/doi.org\/10.1109\/tetci.2023.3300172","journal-title":"IEEE Trans. Emerg. Top. Comput. Intell."},{"key":"3735_CR11","doi-asserted-by":"publisher","first-page":"3936","DOI":"10.1109\/access.2024.3349978","volume":"12","author":"H Liu","year":"2024","unstructured":"Liu, H., Cheng, W., Li, C., Xu, Y., Fan, S.: Lightweight detection model RM-LFPN-YOLO for rebar counting. IEEE Access 12, 3936\u20133947 (2024). https:\/\/doi.org\/10.1109\/access.2024.3349978","journal-title":"IEEE Access"},{"key":"3735_CR12","doi-asserted-by":"publisher","first-page":"1290","DOI":"10.3390\/agriculture12091290","volume":"12","author":"Y Egi","year":"2022","unstructured":"Egi, Y., Hajyzadeh, M., Eyceyurt, E.: Drone-computer communication based tomato generative organ counting model using YOLO V5 and deep-sort. Agriculture 12, 1290 (2022). https:\/\/doi.org\/10.3390\/agriculture12091290","journal-title":"Agriculture"},{"key":"3735_CR13","doi-asserted-by":"publisher","first-page":"9129","DOI":"10.3390\/s23229129","volume":"23","author":"Y Zou","year":"2023","unstructured":"Zou, Y., Tian, Z., Cao, J., Ren, Y., Zhang, Y., Liu, L., Zhang, P., Ni, J.: Rice grain detection and counting method based on TCLE-YOLO model. Sensors 23, 9129 (2023). https:\/\/doi.org\/10.3390\/s23229129","journal-title":"Sensors"},{"key":"3735_CR14","doi-asserted-by":"crossref","unstructured":"Ren, P., Fang, W., Djahel, S.: A novel YOLO-based real-time people counting approach. In: 2017 International Smart Cities Conference (ISC2), pp 1\u20132. IEEE, Wuxi, China (2017)","DOI":"10.1109\/ISC2.2017.8090864"},{"key":"3735_CR15","unstructured":"Redmon, J., Farhadi, A.: YOLOv3: an incremental improvement. arXiv:180402767, (2018)"},{"key":"3735_CR16","unstructured":"Bochkovskiy, A., Wang, C., Liao, H.M.: YOLOv4: optimal speed and accuracy of object detection. arXiv:200410934, (2020)"},{"key":"3735_CR17","doi-asserted-by":"publisher","first-page":"5812","DOI":"10.3390\/app13095812","volume":"13","author":"C Niu","year":"2023","unstructured":"Niu, C., Wang, W., Guo, H., Li, K.: Emergency evacuation simulation study based on improved YOLOv5s and anylogic. Appl. Sci. 13, 5812 (2023). https:\/\/doi.org\/10.3390\/app13095812","journal-title":"Appl. Sci."},{"key":"3735_CR18","unstructured":"Ge, Z., Liu, S., Wang, F., Li, Z., Sun, J.: YOLOX: exceeding YOLO series in 2021. arXiv:210708430, (2021)"},{"key":"3735_CR19","doi-asserted-by":"publisher","first-page":"219","DOI":"10.1109\/ACCESS.2023.3347352","volume":"12","author":"LJ Zhang","year":"2024","unstructured":"Zhang, L.J., Fang, J.J., Liu, Y.X., Le, H.F., Rao, Z.Q., Zhao, J.X.: CR-YOLOv8: multiscale object detection in traffic sign images. IEEE Access 12, 219\u2013228 (2024)","journal-title":"IEEE Access"},{"key":"3735_CR20","doi-asserted-by":"publisher","first-page":"973985","DOI":"10.3389\/fpls.2022.973985","volume":"13","author":"C Wen","year":"2022","unstructured":"Wen, C., Chen, H., Ma, Z., Zhang, T., Yang, C., Su, H., Chen, H.: Pest-YOLO: a model for large-scale multi-class dense and tiny pest detection and counting. Front. Plant Sci. 13, 973985 (2022). https:\/\/doi.org\/10.3389\/fpls.2022.973985","journal-title":"Front. Plant Sci."},{"key":"3735_CR21","doi-asserted-by":"publisher","first-page":"22166","DOI":"10.1109\/tits.2022.3161960","volume":"23","author":"D Ma","year":"2022","unstructured":"Ma, D., Fang, H., Wang, N., Zhang, C., Dong, J., Hu, H.: Automatic detection and counting system for pavement cracks based on PCGAN and YOLO-MF. IEEE Trans. Intell. Transp. Syst. 23, 22166\u201322178 (2022). https:\/\/doi.org\/10.1109\/tits.2022.3161960","journal-title":"IEEE Trans. Intell. Transp. Syst."},{"key":"3735_CR22","doi-asserted-by":"publisher","first-page":"103659","DOI":"10.1016\/j.ijdrr.2023.103659","volume":"91","author":"J Li","year":"2023","unstructured":"Li, J., Hu, Y., Zou, W.: Dynamic risk assessment of emergency evacuation in large public buildings: a case study. Int. J. Disaster Risk Reduct. 91, 103659 (2023). https:\/\/doi.org\/10.1016\/j.ijdrr.2023.103659","journal-title":"Int. J. Disaster Risk Reduct."},{"key":"3735_CR23","doi-asserted-by":"publisher","first-page":"1087","DOI":"10.18280\/ts.380419","volume":"38","author":"J da Wu","year":"2021","unstructured":"da Wu, J., Chen, B.Y., Shyr, W.J., Shih, F.Y.: Vehicle classification and counting system using YOLO object detection technology. Trait. Signal 38, 1087\u20131093 (2021). https:\/\/doi.org\/10.18280\/ts.380419","journal-title":"Trait. Signal"},{"key":"3735_CR24","doi-asserted-by":"publisher","first-page":"905","DOI":"10.1007\/s11760-016-1038-7","volume":"11","author":"H Xu","year":"2016","unstructured":"Xu, H., Zhou, W., Zhu, J., Huang, X., Wang, W.: Vehicle counting based on double virtual lines. Signal Image Video Process 11, 905\u2013912 (2016). https:\/\/doi.org\/10.1007\/s11760-016-1038-7","journal-title":"Signal Image Video Process"},{"key":"3735_CR25","doi-asserted-by":"crossref","unstructured":"Cao, J., Pang, J., Weng, X., Khirodkar, R., Kitani, K.: Observation-centric SORT: rethinking SORT for robust multi-object tracking. arXiv:csCV\/220314360, (2023)","DOI":"10.1109\/CVPR52729.2023.00934"},{"key":"3735_CR26","doi-asserted-by":"publisher","first-page":"4448","DOI":"10.3390\/electronics12214448","volume":"12","author":"D Xu","year":"2023","unstructured":"Xu, D., Wu, Y.: An efficient detector with auxiliary network for remote sensing object detection. Electronics 12, 4448 (2023). https:\/\/doi.org\/10.3390\/electronics12214448","journal-title":"Electronics"},{"key":"3735_CR27","doi-asserted-by":"publisher","DOI":"10.1109\/tnnls.2024.3376563","author":"Q Zhou","year":"2024","unstructured":"Zhou, Q., Shi, H., Xiang, W., Kang, B., Latecki, L.J.: DPNet: dual-path network for real-time object detection with lightweight attention. IEEE Trans. Neural Netw. Learn. Syst. (2024). https:\/\/doi.org\/10.1109\/tnnls.2024.3376563","journal-title":"IEEE Trans. Neural Netw. Learn. Syst."},{"key":"3735_CR28","doi-asserted-by":"crossref","unstructured":"Wang, C.Y., Yeh, I.H., Liao, H.Y.M.: YOLOv9: learning what you want to learn using programmable gradient information. arXiv:csCV\/240213616, (2024)","DOI":"10.1007\/978-3-031-72751-1_1"},{"key":"3735_CR29","doi-asserted-by":"crossref","unstructured":"Misra, D., Nalamada, T., Arasanipalai, A.U., Hou, Q.: Rotate to attend: convolutional triplet attention module. In: 2021 IEEE Winter Conference on Applications of Computer Vision (WACV), pp 3138\u20133147. IEEE, Waikoloa, HI, USA (2021)","DOI":"10.1109\/WACV48630.2021.00318"},{"key":"3735_CR30","doi-asserted-by":"publisher","first-page":"740","DOI":"10.1007\/978-3-319-10602-1_48","volume-title":"Computer Vision \u2013 ECCV 2014","author":"TY Lin","year":"2014","unstructured":"Lin, T.Y., Maire, M., Belongie, S., Hays, J., Perona, P., Ramanan, D., Doll\u00e1r, P., Zitnick, C.L.: Microsoft COCO: common objects in context. In: Fleet, D., Pajdla, T., Schiele, B., Tuytelaars, T. (eds.) Computer Vision \u2013 ECCV 2014, pp. 740\u2013755. Springer, Cham (2014)"},{"key":"3735_CR31","doi-asserted-by":"crossref","unstructured":"Hu, J., Shen, L., Sun, G.: Squeeze-and-excitation networks. In: 2018 IEEE\/CVF Conference on Computer Vision and Pattern Recognition, pp 7132\u20137141. IEEE, Salt Lake City, UT, USA (2018)","DOI":"10.1109\/CVPR.2018.00745"},{"key":"3735_CR32","doi-asserted-by":"crossref","unstructured":"Woo, S., Park, J., Lee, J.Y., Kweon, I.S.: CBAM: convolutional block attention module. arXiv:180706521, (2018)","DOI":"10.1007\/978-3-030-01234-2_1"},{"key":"3735_CR33","doi-asserted-by":"crossref","unstructured":"Hou, Q., Zhou, D., Feng, J.: Coordinate attention for efficient mobile network design. In: 2021 IEEE\/CVF Conference on Computer Vision and Pattern Recognition (CVPR), pp 13708\u201313717. IEEE, Nashville, TN, USA (2021)","DOI":"10.1109\/CVPR46437.2021.01350"},{"key":"3735_CR34","doi-asserted-by":"crossref","unstructured":"Wang, Q., Wu, B., Zhu, P., Li, P., Zuo, W., Hu, Q.: ECA-Net: efficient channel attention for deep convolutional neural networks. In: 2020 IEEE\/CVF Conference on Computer Vision and Pattern Recognition (CVPR), pp 11531\u201311539. IEEE, Seattle, WA, USA (2020)","DOI":"10.1109\/CVPR42600.2020.01155"},{"key":"3735_CR35","doi-asserted-by":"crossref","unstructured":"Ouyang, D., He, S., Zhang, G., Luo, M., Guo, H., Zhan, J., Huang, Z.: Efficient multi-scale attention module with cross-spatial learning. In: ICASSP 2023 - 2023 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), pp 1\u20135. IEEE, Rhodes Island, Greece (2023)","DOI":"10.1109\/ICASSP49357.2023.10096516"},{"key":"3735_CR36","doi-asserted-by":"crossref","unstructured":"Liu, W., Anguelov, D., Erhan, D., Szegedy, C., Reed, S., Fu, C.Y., Berg, A.C.: SSD: single shot multibox detector. arXiv:151202325 (2015)","DOI":"10.1007\/978-3-319-46448-0_2"}],"container-title":["Signal, Image and Video Processing"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s11760-024-03735-8.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1007\/s11760-024-03735-8\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s11760-024-03735-8.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,1,28]],"date-time":"2025-01-28T17:52:33Z","timestamp":1738086753000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/s11760-024-03735-8"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2024,12,5]]},"references-count":36,"journal-issue":{"issue":"1","published-print":{"date-parts":[[2025,1]]}},"alternative-id":["3735"],"URL":"https:\/\/doi.org\/10.1007\/s11760-024-03735-8","relation":{},"ISSN":["1863-1703","1863-1711"],"issn-type":[{"type":"print","value":"1863-1703"},{"type":"electronic","value":"1863-1711"}],"subject":[],"published":{"date-parts":[[2024,12,5]]},"assertion":[{"value":"29 July 2024","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"12 October 2024","order":2,"name":"revised","label":"Revised","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"20 November 2024","order":3,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"5 December 2024","order":4,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}},{"order":1,"name":"Ethics","group":{"name":"EthicsHeading","label":"Declarations"}},{"value":"The authors declare no competing interests.","order":2,"name":"Ethics","group":{"name":"EthicsHeading","label":"Conflict of interests"}}],"article-number":"62"}}