{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,12]],"date-time":"2026-03-12T22:48:23Z","timestamp":1773355703508,"version":"3.50.1"},"reference-count":38,"publisher":"Springer Science and Business Media LLC","issue":"4","license":[{"start":{"date-parts":[[2023,6,12]],"date-time":"2023-06-12T00:00:00Z","timestamp":1686528000000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2023,6,12]],"date-time":"2023-06-12T00:00:00Z","timestamp":1686528000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"}],"funder":[{"name":"Key-Area Research and Development Program of Guangdong Province","award":["2020B0909020001"],"award-info":[{"award-number":["2020B0909020001"]}]},{"name":"Key-Area Research and Development Program of Guangdong Province","award":["2020B0909020001"],"award-info":[{"award-number":["2020B0909020001"]}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"crossref","award":["61573113"],"award-info":[{"award-number":["61573113"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"crossref"}]}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["J Real-Time Image Proc"],"published-print":{"date-parts":[[2023,8]]},"DOI":"10.1007\/s11554-023-01329-0","type":"journal-article","created":{"date-parts":[[2023,6,12]],"date-time":"2023-06-12T11:02:23Z","timestamp":1686567743000},"update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":19,"title":["L-YOLOv4: lightweight YOLOv4 based on modified RFB-s and depthwise separable convolution for multi-target detection in complex scenes"],"prefix":"10.1007","volume":"20","author":[{"given":"Peng","family":"Ding","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Huaming","family":"Qian","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jiabing","family":"Bao","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yipeng","family":"Zhou","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Shuya","family":"Yan","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2023,6,12]]},"reference":[{"key":"1329_CR1","unstructured":"Bochkovskiy, A., Wang, C., Liao, H.M.: Yolov4: optimal speed and accuracy of object detection. CoRR (2020). arXiv:2004.10934"},{"key":"1329_CR2","doi-asserted-by":"crossref","unstructured":"Dai, X., Chen, Y., Xiao, B., Chen, D., Liu, M., Yuan, L., Zhang, L.: Dynamic head: unifying object detection heads with attentions. In: Computer Vision Foundation\/IEEE, pp. 7373\u20137382 (2021)","DOI":"10.1109\/CVPR46437.2021.00729"},{"issue":"3","key":"1329_CR3","doi-asserted-by":"publisher","first-page":"487","DOI":"10.1007\/s11554-022-01201-7","volume":"19","author":"P Ding","year":"2022","unstructured":"Ding, P., Qian, H., Chu, S.: Slimyolov4: lightweight object detector based on yolov4. J. Real Time Image Process. 19(3), 487\u2013498 (2022). https:\/\/doi.org\/10.1007\/s11554-022-01201-7","journal-title":"J. Real Time Image Process."},{"issue":"2","key":"1329_CR4","doi-asserted-by":"publisher","first-page":"34","DOI":"10.1007\/s11554-023-01263-1","volume":"20","author":"P Ding","year":"2023","unstructured":"Ding, P., Qian, H., Zhou, Y., Chu, S.: Object detection method based on lightweight yolov4 and attention mechanism in security scenes. J. Real Time Image Process. 20(2), 34 (2023). https:\/\/doi.org\/10.1007\/s11554-023-01263-1","journal-title":"J. Real Time Image Process."},{"key":"1329_CR5","doi-asserted-by":"crossref","unstructured":"Girshick, R.: Fast r-cnn. In: Proceedings of the IEEE International Conference on Computer Vision, pp. 1440\u20131448 (2015)","DOI":"10.1109\/ICCV.2015.169"},{"key":"1329_CR6","doi-asserted-by":"crossref","unstructured":"Girshick, R., Donahue, J., Darrell, T., Malik, J.: Rich feature hierarchies for accurate object detection and semantic segmentation. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, pp. 580\u2013587 (2014)","DOI":"10.1109\/CVPR.2014.81"},{"key":"1329_CR7","doi-asserted-by":"crossref","unstructured":"Hou, Q., Zhou, D., Feng, J.: Coordinate attention for efficient mobile network design. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, pp. 13713\u201313722 (2021)","DOI":"10.1109\/CVPR46437.2021.01350"},{"key":"1329_CR8","doi-asserted-by":"crossref","unstructured":"Howard, A., Sandler, M., Chu, G., Chen, L.C., Chen, B., Tan, M., Wang, W., Zhu, Y., Pang, R., Vasudevan, V., et\u00a0al.: Searching for mobilenetv3. In: Proceedings of the IEEE\/CVF International Conference on Computer Vision, pp. 1314\u20131324 (2019)","DOI":"10.1109\/ICCV.2019.00140"},{"key":"1329_CR9","unstructured":"Howard, A.G., Zhu, M., Chen, B., Kalenichenko, D., Wang, W., Weyand, T., Andreetto, M., Adam, H.: Mobilenets: Efficient convolutional neural networks for mobile vision applications (2017). arXiv preprint arXiv:1704.04861"},{"key":"1329_CR10","doi-asserted-by":"crossref","unstructured":"Hu, J., Shen, L., Sun, G.: Squeeze-and-excitation networks. CoRR (2017). arXiv:1709.01507","DOI":"10.1109\/CVPR.2018.00745"},{"key":"1329_CR11","doi-asserted-by":"crossref","unstructured":"Hu, J., Shen, L., Sun, G.: Squeeze-and-excitation networks. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, pp. 7132\u20137141 (2018)","DOI":"10.1109\/CVPR.2018.00745"},{"key":"1329_CR12","unstructured":"Iandola, F., Moskewicz, M., Karayev, S., Girshick, R., Darrell, T., Keutzer, K.: Densenet: implementing efficient convnet descriptor pyramids (2014). arXiv preprint arXiv:1404.1869"},{"key":"1329_CR13","doi-asserted-by":"publisher","first-page":"85740","DOI":"10.1109\/ACCESS.2020.2992532","volume":"8","author":"G Jin","year":"2020","unstructured":"Jin, G., Taniguchi, R., Qu, F.: Auxiliary detection head for one-stage object detection. IEEE Access 8, 85740\u201385749 (2020). https:\/\/doi.org\/10.1109\/ACCESS.2020.2992532","journal-title":"IEEE Access"},{"issue":"2","key":"1329_CR14","doi-asserted-by":"publisher","first-page":"294","DOI":"10.5755\/j01.itc.51.2.30667","volume":"51","author":"X Li","year":"2022","unstructured":"Li, X., Yun, X., Zhao, Z., Zhang, K., Wang, X.: Lightweight deeplearning method for multi-vehicle object recognition. Inf. Technol. Control. 51(2), 294\u2013312 (2022). https:\/\/doi.org\/10.5755\/j01.itc.51.2.30667","journal-title":"Inf. Technol. Control."},{"key":"1329_CR15","doi-asserted-by":"crossref","unstructured":"Lin, T.Y., Doll\u00e1r, P., Girshick, R., He, K., Hariharan, B., Belongie, S.: Feature pyramid networks for object detection. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, pp. 2117\u20132125 (2017)","DOI":"10.1109\/CVPR.2017.106"},{"key":"1329_CR16","doi-asserted-by":"publisher","unstructured":"Liu, S., Huang, D., Wang, Y.: Receptive field block net for accurate and fast object detection. In: Computer Vision\u2014ECCV 2018\u201415th European Conference, Munich, Germany, September 8\u201314, 2018, Proceedings, Part XI, Lecture Notes in Computer Science, vol. 11215. Springer, pp. 404\u2013419 (2018). https:\/\/doi.org\/10.1007\/978-3-030-01252-6_24","DOI":"10.1007\/978-3-030-01252-6_24"},{"key":"1329_CR17","doi-asserted-by":"publisher","unstructured":"Liu, W., Anguelov, D., Erhan, D., Szegedy, C., Reed, S.E., Fu, C., Berg, A.C.: SSD: single shot multibox detector. In: B.\u00a0Leibe, J.\u00a0Matas, N.\u00a0Sebe, M.\u00a0Welling (eds.) Computer Vision\u2014ECCV 2016\u201414th European Conference, Amsterdam, The Netherlands, October 11\u201314, 2016, Proceedings, Part I, Lecture Notes in Computer Science, vol. 9905. Springer, pp. 21\u201337 (2016). https:\/\/doi.org\/10.1007\/978-3-319-46448-0_2","DOI":"10.1007\/978-3-319-46448-0_2"},{"key":"1329_CR18","doi-asserted-by":"crossref","unstructured":"Ma, N., Zhang, X., Zheng, H.T., Sun, J.: Shufflenet v2: practical guidelines for efficient cnn architecture design. In: Proceedings of the European Conference on Computer Vision (ECCV), pp. 116\u2013131 (2018)","DOI":"10.1007\/978-3-030-01264-9_8"},{"issue":"3","key":"1329_CR19","doi-asserted-by":"publisher","first-page":"1098","DOI":"10.3390\/s22031098","volume":"22","author":"H Masood","year":"2022","unstructured":"Masood, H., Zafar, A., Ali, M.U., Hussain, T., Khan, M.A., Tariq, U., Damasevicius, R.: Tracking of a fixed-shape moving object based on the gradient descent method. Sensors 22(3), 1098 (2022). https:\/\/doi.org\/10.3390\/s22031098","journal-title":"Sensors"},{"key":"1329_CR20","unstructured":"Purkait, P., Zhao, C., Zach, C.: Spp-net: deep absolute pose regression with synthetic views (2017). arXiv preprint arXiv:1712.03452"},{"key":"1329_CR21","doi-asserted-by":"crossref","unstructured":"Redmon, J., Divvala, S., Girshick, R., Farhadi, A.: You only look once: unified, real-time object detection. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, pp. 779\u2013788 (2016)","DOI":"10.1109\/CVPR.2016.91"},{"key":"1329_CR22","doi-asserted-by":"crossref","unstructured":"Redmon, J., Farhadi, A.: Yolo9000: better, faster, stronger. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, pp. 7263\u20137271 (2017)","DOI":"10.1109\/CVPR.2017.690"},{"key":"1329_CR23","unstructured":"Redmon, J., Farhadi, A.: Yolov3: an incremental improvement (2018). arXiv preprint arXiv:1804.02767"},{"key":"1329_CR24","first-page":"91","volume":"28","author":"S Ren","year":"2015","unstructured":"Ren, S., He, K., Girshick, R., Sun, J.: Faster r-cnn: towards real-time object detection with region proposal networks. Adv Neural Inf Process Syst 28, 91\u201399 (2015)","journal-title":"Adv Neural Inf Process Syst"},{"key":"1329_CR25","unstructured":"Ren, S., He, K., Girshick, R.B., Sun, J.: Faster R-CNN: towards real-time object detection with region proposal networks, pp. 91\u201399 (2015)"},{"key":"1329_CR26","doi-asserted-by":"crossref","unstructured":"Sandler, M., Howard, A., Zhu, M., Zhmoginov, A., Chen, L.C.: Mobilenetv2: inverted residuals and linear bottlenecks. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, pp. 4510\u20134520 (2018)","DOI":"10.1109\/CVPR.2018.00474"},{"key":"1329_CR27","unstructured":"Sharma, S., Kiros, R., Salakhutdinov, R.: Action recognition using visual attention. CoRR (2015). arXiv:1511.04119"},{"issue":"1","key":"1329_CR28","doi-asserted-by":"publisher","first-page":"13","DOI":"10.5755\/j01.itc.50.1.25094","volume":"50","author":"B Shi","year":"2021","unstructured":"Shi, B., Li, X., Nie, T., Zhang, K., Wang, W.: Multi-object recognition method based on improved yolov2 model. Inf. Technol. Control. 50(1), 13\u201327 (2021). https:\/\/doi.org\/10.5755\/j01.itc.50.1.25094","journal-title":"Inf. Technol. Control."},{"key":"1329_CR29","unstructured":"Simonyan, K., Zisserman, A.: Very deep convolutional networks for large-scale image recognition (2014). arXiv preprint arXiv:1409.1556"},{"issue":"1","key":"1329_CR30","doi-asserted-by":"publisher","first-page":"89","DOI":"10.5755\/j01.itc.50.1.27987","volume":"50","author":"Z Sun","year":"2021","unstructured":"Sun, Z., Zhao, M., Jia, B.: A GF-3 SAR image dataset of road segmentation. Inf. Technol. Control. 50(1), 89\u2013101 (2021). https:\/\/doi.org\/10.5755\/j01.itc.50.1.27987","journal-title":"Inf. Technol. Control."},{"key":"1329_CR31","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 2020, Seattle, WA, USA, June 13\u201319, 2020, pp. 11531\u201311539. Computer Vision Foundation\/IEEE (2020)","DOI":"10.1109\/CVPR42600.2020.01155"},{"key":"1329_CR32","doi-asserted-by":"crossref","unstructured":"Woo, S., Park, J., Lee, J.Y., Kweon, I.S.: Cbam: convolutional block attention module. In: Proceedings of the European Conference on Computer Vision (ECCV), pp. 3\u201319 (2018)","DOI":"10.1007\/978-3-030-01234-2_1"},{"key":"1329_CR33","doi-asserted-by":"crossref","unstructured":"Wu, Y., Chen, Y., Yuan, L., Liu, Z., Wang, L., Li, H., Fu, Y.: Rethinking classification and localization for object detection. In: 2020 IEEE\/CVF Conference on Computer Vision and Pattern Recognition, CVPR 2020, Seattle, WA, USA, June 13\u201319, 2020. Computer Vision Foundation\/IEEE, pp. 10183\u201310192 (2020)","DOI":"10.1109\/CVPR42600.2020.01020"},{"key":"1329_CR34","doi-asserted-by":"crossref","unstructured":"Zhang, X., Zhou, X., Lin, M., Sun, J.: Shufflenet: an extremely efficient convolutional neural network for mobile devices. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, pp. 6848\u20136856 (2018)","DOI":"10.1109\/CVPR.2018.00716"},{"issue":"4","key":"1329_CR35","doi-asserted-by":"publisher","first-page":"715","DOI":"10.1007\/s11554-022-01217-z","volume":"19","author":"Q Zhao","year":"2022","unstructured":"Zhao, Q., Peng, Q., Zhuang, Y.: Lane line detection based on the codec structure of the attention mechanism. J. Real Time Image Process. 19(4), 715\u2013726 (2022). https:\/\/doi.org\/10.1007\/s11554-022-01217-z","journal-title":"J. Real Time Image Process."},{"issue":"22","key":"1329_CR36","doi-asserted-by":"publisher","first-page":"4855","DOI":"10.3390\/s19224855","volume":"19","author":"B Zhou","year":"2019","unstructured":"Zhou, B., Duan, X., Ye, D., Wei, W., Wozniak, M., Polap, D., Damasevicius, R.: Multi-level features extraction for discontinuous target tracking in remote sensing image monitoring. Sensors 19(22), 4855 (2019). https:\/\/doi.org\/10.3390\/s19224855","journal-title":"Sensors"},{"key":"1329_CR37","doi-asserted-by":"crossref","unstructured":"Zhou, D., Hou, Q., Chen, Y., Feng, J., Yan, S.: Rethinking bottleneck structure for efficient mobile network design. Springer, pp. 680\u2013697 (2020)","DOI":"10.1007\/978-3-030-58580-8_40"},{"issue":"3","key":"1329_CR38","doi-asserted-by":"publisher","first-page":"485","DOI":"10.5755\/j01.itc.51.3.30540","volume":"51","author":"X Zhou","year":"2022","unstructured":"Zhou, X., Yi, J., Xie, G., Jia, Y., Xu, G., Sun, M.: Human detection algorithm based on improved YOLO v4. Inf. Technol. Control. 51(3), 485\u2013498 (2022). https:\/\/doi.org\/10.5755\/j01.itc.51.3.30540","journal-title":"Inf. Technol. Control."}],"container-title":["Journal of Real-Time Image Processing"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s11554-023-01329-0.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1007\/s11554-023-01329-0\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s11554-023-01329-0.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2023,7,24]],"date-time":"2023-07-24T19:23:09Z","timestamp":1690226589000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/s11554-023-01329-0"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2023,6,12]]},"references-count":38,"journal-issue":{"issue":"4","published-print":{"date-parts":[[2023,8]]}},"alternative-id":["1329"],"URL":"https:\/\/doi.org\/10.1007\/s11554-023-01329-0","relation":{},"ISSN":["1861-8200","1861-8219"],"issn-type":[{"value":"1861-8200","type":"print"},{"value":"1861-8219","type":"electronic"}],"subject":[],"published":{"date-parts":[[2023,6,12]]},"assertion":[{"value":"17 February 2023","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"31 May 2023","order":2,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"12 June 2023","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 authors declare that they have no conflict of interest.","order":2,"name":"Ethics","group":{"name":"EthicsHeading","label":"Conflict of interest"}}],"article-number":"71"}}