{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,1,6]],"date-time":"2026-01-06T15:38:48Z","timestamp":1767713928115,"version":"3.48.0"},"reference-count":47,"publisher":"Springer Science and Business Media LLC","issue":"2","license":[{"start":{"date-parts":[[2026,1,6]],"date-time":"2026-01-06T00:00:00Z","timestamp":1767657600000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2026,1,6]],"date-time":"2026-01-06T00:00:00Z","timestamp":1767657600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["Cluster Comput"],"published-print":{"date-parts":[[2026,4]]},"DOI":"10.1007\/s10586-025-05821-z","type":"journal-article","created":{"date-parts":[[2026,1,6]],"date-time":"2026-01-06T15:32:48Z","timestamp":1767713568000},"update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["SOO-YOLO: an efficient small object detection model for UAV images"],"prefix":"10.1007","volume":"29","author":[{"given":"Renjie","family":"Chen","sequence":"first","affiliation":[]},{"given":"Hua","family":"Sun","sequence":"additional","affiliation":[]},{"given":"Haiyang","family":"Fan","sequence":"additional","affiliation":[]},{"given":"Pingxiang","family":"Wu","sequence":"additional","affiliation":[]},{"given":"Zhenqi","family":"Zhang","sequence":"additional","affiliation":[]},{"given":"Yang","family":"Chen","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2026,1,6]]},"reference":[{"issue":"9","key":"5821_CR1","doi-asserted-by":"publisher","first-page":"13379","DOI":"10.1007\/s10586-024-04595-0","volume":"27","author":"Y Li","year":"2024","unstructured":"Li, Y., Li, H.: A novel real-time object detection method for complex road scenes based on yolov7-tiny. Cluster Computing 27(9), 13379\u201313393 (2024)","journal-title":"Cluster Computing"},{"issue":"7","key":"5821_CR2","doi-asserted-by":"publisher","first-page":"9735","DOI":"10.1007\/s10586-024-04504-5","volume":"27","author":"A Sabino","year":"2024","unstructured":"Sabino, A., Lima, L.N., Brito, C., Feitosa, L., Caetano, M.F., Barreto, P.S., Silva, F.A.: Forest fire monitoring system supported by unmanned aerial vehicles and edge computing: a performance evaluation using petri nets. Cluster Computing 27(7), 9735\u20139755 (2024)","journal-title":"Cluster Computing"},{"issue":"2","key":"5821_CR3","doi-asserted-by":"publisher","first-page":"1297","DOI":"10.1007\/s10586-022-03627-x","volume":"26","author":"A Bouguettaya","year":"2023","unstructured":"Bouguettaya, A., Zarzour, H., Kechida, A., Taberkit, A.M.: A survey on deep learning-based identification of plant and crop diseases from uav-based aerial images. Cluster Computing 26(2), 1297\u20131317 (2023)","journal-title":"Cluster Computing"},{"key":"5821_CR4","first-page":"1","volume":"73","author":"J Shen","year":"2024","unstructured":"Shen, J., Liu, N., Sun, H., Li, D., Zhang, Y.: An instrument indication acquisition algorithm based on lightweight deep convolutional neural network and hybrid attention fine-grained features. IEEE Trans. Instrum. Meas. 73, 1\u201316 (2024)","journal-title":"IEEE Trans. Instrum. Meas."},{"issue":"1","key":"5821_CR5","doi-asserted-by":"publisher","DOI":"10.1038\/s40494-025-01565-6","volume":"13","author":"J Shen","year":"2025","unstructured":"Shen, J., Liu, N., Sun, H., Li, D., Zhang, Y., Han, L.: An algorithm based on lightweight semantic features for ancient mural element object detection. npj Heritage Science 13(1), 70 (2025)","journal-title":"npj Heritage Science"},{"key":"5821_CR6","first-page":"1","volume":"71","author":"J Shen","year":"2021","unstructured":"Shen, J., Liu, N., Xu, C., Sun, H., Xiao, Y., Li, D., Zhang, Y.: Finger vein recognition algorithm based on lightweight deep convolutional neural network. IEEE Trans. Instrum. Meas. 71, 1\u201313 (2021)","journal-title":"IEEE Trans. Instrum. Meas."},{"key":"5821_CR7","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":"5821_CR8","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":"5821_CR9","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. In: Computer Vision\u2013ECCV 2016: 14th European Conference, Amsterdam, The Netherlands, October 11\u201314, 2016, Proceedings, Part I 14, pp. 21\u201337 (2016). Springer","DOI":"10.1007\/978-3-319-46448-0_2"},{"key":"5821_CR10","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":"5821_CR11","doi-asserted-by":"crossref","unstructured":"Huang, Y.-X., Liu, H.-I., Shuai, H.-H., Cheng, W.-H.: Dq-detr: Detr with dynamic query for tiny object detection. In: European Conference on Computer Vision, pp. 290\u2013305 (2024). Springer","DOI":"10.1007\/978-3-031-73116-7_17"},{"key":"5821_CR12","doi-asserted-by":"crossref","unstructured":"Sun, H., Wang, R., Li, Y., Yang, L., Lin, S., Cao, X., Zhang, B.: Set: Spectral enhancement for tiny object detection. In: Proceedings of the Computer Vision and Pattern Recognition Conference, pp. 4713\u20134723 (2025)","DOI":"10.1109\/CVPR52734.2025.00444"},{"key":"5821_CR13","doi-asserted-by":"crossref","unstructured":"Cao, B., Yao, H., Zhu, P., Hu, Q.: Visible and clear: Finding tiny objects in difference map. In: European Conference on Computer Vision, pp. 1\u201318 (2024). Springer","DOI":"10.1007\/978-3-031-72643-9_1"},{"key":"5821_CR14","doi-asserted-by":"publisher","first-page":"4643","DOI":"10.1609\/aaai.v39i5.32490","volume":"39","author":"C Li","year":"2025","unstructured":"Li, C., Zhao, R., Wang, Z., Xu, H., Zhu, X.: Remdet: Rethinking efficient model design for uav object detection. Proceedings of the AAAI Conference on Artificial Intelligence 39, 4643\u20134651 (2025)","journal-title":"Proceedings of the AAAI Conference on Artificial Intelligence"},{"key":"5821_CR15","doi-asserted-by":"publisher","first-page":"8673","DOI":"10.1609\/aaai.v39i8.32937","volume":"39","author":"Y Xiao","year":"2025","unstructured":"Xiao, Y., Xu, T., Xin, Y., Li, J.: Fbrt-yolo: Faster and better for real-time aerial image detection. Proceedings of the AAAI Conference on Artificial Intelligence 39, 8673\u20138681 (2025)","journal-title":"Proceedings of the AAAI Conference on Artificial Intelligence"},{"key":"5821_CR16","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":"5821_CR17","doi-asserted-by":"crossref","unstructured":"Liu, S., Qi, L., Qin, H., Shi, J., Jia, J.: Path aggregation network for instance segmentation. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, pp. 8759\u20138768 (2018)","DOI":"10.1109\/CVPR.2018.00913"},{"key":"5821_CR18","doi-asserted-by":"crossref","unstructured":"Tan, M., Pang, R., Le, Q.V.: Efficientdet: Scalable and efficient object detection. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, pp. 10781\u201310790 (2020)","DOI":"10.1109\/CVPR42600.2020.01079"},{"key":"5821_CR19","doi-asserted-by":"crossref","unstructured":"Yang, M., Yu, K., Zhang, C., Li, Z., Yang, K.: Denseaspp for semantic segmentation in street scenes. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, pp. 3684\u20133692 (2018)","DOI":"10.1109\/CVPR.2018.00388"},{"key":"5821_CR20","doi-asserted-by":"crossref","unstructured":"Yang, G., Lei, J., Zhu, Z., Cheng, S., Feng, Z., Liang, R.: Afpn: Asymptotic feature pyramid network for object detection. In: 2023 IEEE International Conference on Systems, Man, and Cybernetics (SMC), pp. 2184\u20132189 (2023). IEEE","DOI":"10.1109\/SMC53992.2023.10394415"},{"key":"5821_CR21","doi-asserted-by":"publisher","first-page":"4341","DOI":"10.1109\/TIP.2023.3297408","volume":"32","author":"Y Quan","year":"2023","unstructured":"Quan, Y., Zhang, D., Zhang, L., Tang, J.: Centralized feature pyramid for object detection. IEEE Transactions on Image Processing 32, 4341\u20134354 (2023)","journal-title":"IEEE Transactions on Image Processing"},{"key":"5821_CR22","doi-asserted-by":"crossref","unstructured":"Lin, T.-Y., Goyal, P., Girshick, R., He, K., Doll\u00e1r, P.: Focal loss for dense object detection. In: Proceedings of the IEEE International Conference on Computer Vision, pp. 2980\u20132988 (2017)","DOI":"10.1109\/ICCV.2017.324"},{"key":"5821_CR23","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: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, pp. 7373\u20137382 (2021)","DOI":"10.1109\/CVPR46437.2021.00729"},{"key":"5821_CR24","doi-asserted-by":"crossref","unstructured":"Feng, C., Zhong, Y., Gao, Y., Scott, M.R., Huang, W.: Tood: Task-aligned one-stage object detection. In: 2021 IEEE\/CVF International Conference on Computer Vision (ICCV), pp. 3490\u20133499 (2021). IEEE Computer Society","DOI":"10.1109\/ICCV48922.2021.00349"},{"key":"5821_CR25","unstructured":"Khanam, R., Hussain, M.: Yolov11: An overview of the key architectural enhancements. arXiv preprint arXiv:2410.17725 (2024)"},{"key":"5821_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":"5821_CR27","unstructured":"Liu, Y., Shao, Z., Teng, Y., Hoffmann, N.: Nam: Normalization-based attention module. arXiv preprint arXiv:2111.12419 (2021)"},{"key":"5821_CR28","doi-asserted-by":"publisher","DOI":"10.1016\/j.eswa.2025.126440","volume":"269","author":"H Wang","year":"2025","unstructured":"Wang, H., Liu, J., Zhao, J., Zhang, J., Zhao, D.: Precision and speed: Lsod-yolo for lightweight small object detection. Expert Systems with Applications 269, 126440 (2025)","journal-title":"Expert Systems with Applications"},{"key":"5821_CR29","doi-asserted-by":"publisher","DOI":"10.1016\/j.patcog.2023.109819","volume":"143","author":"G Xu","year":"2023","unstructured":"Xu, G., Liao, W., Zhang, X., Li, C., He, X., Wu, X.: Haar wavelet downsampling: A simple but effective downsampling module for semantic segmentation. Pattern Recognition 143, 109819 (2023)","journal-title":"Pattern Recognition"},{"key":"5821_CR30","doi-asserted-by":"crossref","unstructured":"Ding, X., Zhang, X., Han, J., Ding, G.: Scaling up your kernels to 31x31: Revisiting large kernel design in cnns. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, pp. 11963\u201311975 (2022)","DOI":"10.1109\/CVPR52688.2022.01166"},{"key":"5821_CR31","doi-asserted-by":"publisher","DOI":"10.1016\/j.neucom.2025.129655","volume":"631","author":"X Ren","year":"2025","unstructured":"Ren, X., Deng, Z., Ye, J., He, J., Yang, D.: Fcn+: Global receptive convolution makes fcn great again. Neurocomputing 631, 129655 (2025)","journal-title":"Neurocomputing"},{"key":"5821_CR32","doi-asserted-by":"crossref","unstructured":"Tian, Z., Shen, C., Chen, H., He, T.: Fcos: Fully convolutional one-stage object detection. In: Proceedings of the IEEE\/CVF International Conference on Computer Vision, pp. 9627\u20139636 (2019)","DOI":"10.1109\/ICCV.2019.00972"},{"key":"5821_CR33","doi-asserted-by":"crossref","unstructured":"Dai, J., Qi, H., Xiong, Y., Li, Y., Zhang, G., Hu, H., Wei, Y.: Deformable convolutional networks. In: Proceedings of the IEEE International Conference on Computer Vision, pp. 764\u2013773 (2017)","DOI":"10.1109\/ICCV.2017.89"},{"key":"5821_CR34","unstructured":"Tong, Z., Chen, Y., Xu, Z., Yu, R.: Wise-iou: bounding box regression loss with dynamic focusing mechanism. arXiv preprint arXiv:2301.10051 (2023)"},{"issue":"2","key":"5821_CR35","doi-asserted-by":"publisher","DOI":"10.1007\/s10586-024-04823-7","volume":"28","author":"F Wang","year":"2025","unstructured":"Wang, F., Li, D., Zhang, J., Wang, X., Li, L., Shi, X.: Multiple adaptive fusion network with mittag leffler iou loss for aircraft detection in remote sensing images. Cluster Computing 28(2), 76 (2025)","journal-title":"Cluster Computing"},{"key":"5821_CR36","unstructured":"Zhang, H., Xu, C., Zhang, S.: Inner-iou: more effective intersection over union loss with auxiliary bounding box. arXiv preprint arXiv:2311.02877 (2023)"},{"key":"5821_CR37","unstructured":"Ma, S., Xu, Y.: Mpdiou: a loss for efficient and accurate bounding box regression. arXiv preprint arXiv:2307.07662 (2023)"},{"key":"5821_CR38","unstructured":"Lee, J., Park, S., Mo, S., Ahn, S., Shin, J.: Layer-adaptive sparsity for the magnitude-based pruning. arXiv preprint arXiv:2010.07611 (2020)"},{"key":"5821_CR39","doi-asserted-by":"crossref","unstructured":"He, K., Gkioxari, G., Doll\u00e1r, P., Girshick, R.: Mask r-cnn. In: Proceedings of the IEEE International Conference on Computer Vision, pp. 2961\u20132969 (2017)","DOI":"10.1109\/ICCV.2017.322"},{"key":"5821_CR40","doi-asserted-by":"crossref","unstructured":"Cai, Z., Vasconcelos, N.: Cascade r-cnn: Delving into high quality object detection. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, pp. 6154\u20136162 (2018)","DOI":"10.1109\/CVPR.2018.00644"},{"key":"5821_CR41","first-page":"51094","volume":"36","author":"C Wang","year":"2023","unstructured":"Wang, C., He, W., Nie, Y., Guo, J., Liu, C., Wang, Y., Han, K.: Gold-yolo: Efficient object detector via gather-and-distribute mechanism. Adv. Neural. Inf. Process. Syst. 36, 51094\u201351112 (2023)","journal-title":"Adv. Neural. Inf. Process. Syst."},{"key":"5821_CR42","doi-asserted-by":"crossref","unstructured":"Liu, S., Zha, J., Sun, J., Li, Z., Wang, G.: Edgeyolo: An edge-real-time object detector. In: 2023 42nd Chinese Control Conference (CCC), pp. 7507\u20137512 (2023). IEEE","DOI":"10.23919\/CCC58697.2023.10239786"},{"key":"5821_CR43","unstructured":"Xu, X., Jiang, Y., Chen, W., Huang, Y., Zhang, Y., Sun, X.: Damo-yolo: A report on real-time object detection design. arXiv preprint arXiv:2211.15444 (2022)"},{"key":"5821_CR44","doi-asserted-by":"publisher","DOI":"10.1109\/TPAMI.2024.3524377","author":"Y Feng","year":"2025","unstructured":"Feng, Y., Huang, J., Du, S., Ying, S., Yong, J.-H., Li, Y., Ding, G., Ji, R., Gao, Y.: Hyper-yolo: When visual object detection meets hypergraph computation. IEEE Transactions on Pattern Analysis and Machine Intelligence (2025). https:\/\/doi.org\/10.1109\/TPAMI.2024.3524377","journal-title":"IEEE Transactions on Pattern Analysis and Machine Intelligence"},{"key":"5821_CR45","doi-asserted-by":"crossref","unstructured":"Selvaraju, R.R., Cogswell, M., Das, A., Vedantam, R., Parikh, D., Batra, D.: Grad-cam: Visual explanations from deep networks via gradient-based localization. In: Proceedings of the IEEE International Conference on Computer Vision, pp. 618\u2013626 (2017)","DOI":"10.1109\/ICCV.2017.74"},{"key":"5821_CR46","unstructured":"Liu, S., Huang, D., Wang, Y.: Learning spatial fusion for single-shot object detection. arxiv 2019. arXiv preprint arXiv:1911.09516 (1911)"},{"key":"5821_CR47","unstructured":"Ren, S., He, K., Girshick, R., Sun, J.: Faster r-cnn: Towards real-time object detection with region proposal networks. Advances in neural information processing systems 28 (2015)"}],"container-title":["Cluster Computing"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s10586-025-05821-z.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1007\/s10586-025-05821-z","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s10586-025-05821-z.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,1,6]],"date-time":"2026-01-06T15:32:54Z","timestamp":1767713574000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/s10586-025-05821-z"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026,1,6]]},"references-count":47,"journal-issue":{"issue":"2","published-print":{"date-parts":[[2026,4]]}},"alternative-id":["5821"],"URL":"https:\/\/doi.org\/10.1007\/s10586-025-05821-z","relation":{},"ISSN":["1386-7857","1573-7543"],"issn-type":[{"value":"1386-7857","type":"print"},{"value":"1573-7543","type":"electronic"}],"subject":[],"published":{"date-parts":[[2026,1,6]]},"assertion":[{"value":"15 April 2025","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"30 September 2025","order":2,"name":"revised","label":"Revised","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"22 October 2025","order":3,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"6 January 2026","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":"Competing interests"}},{"value":"Not applicable.","order":3,"name":"Ethics","group":{"name":"EthicsHeading","label":"Ethics declaration"}}],"article-number":"83"}}