{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,17]],"date-time":"2026-06-17T16:36:52Z","timestamp":1781714212809,"version":"3.54.5"},"reference-count":62,"publisher":"MDPI AG","issue":"2","license":[{"start":{"date-parts":[[2026,2,6]],"date-time":"2026-02-06T00:00:00Z","timestamp":1770336000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"Collaborative Innovation Platform Project of the Fuzhou\u2013Xiamen\u2013Quanzhou National Independent Innovation Demonstration Zone","award":["2023FX0002"],"award-info":[{"award-number":["2023FX0002"]}]},{"name":"STS Project of the Fujian Science and Technology Program","award":["2024T3102"],"award-info":[{"award-number":["2024T3102"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["J. Imaging"],"abstract":"<jats:p>Unmanned aerial vehicles (UAVs) are now widely used in various applications, including agriculture, urban traffic management, and search and rescue operations. However, several challenges arise, including the small size of objects occupying only a sparse number of pixels in images, complex backgrounds in aerial footage, and limited computational resources onboard. To address these issues, this paper proposes an improved UAV-based small object detection algorithm, YOLO11s-UAV, specifically designed for aerial imagery. Firstly, we introduce a novel FPN, called Content-Aware Reassembly and Interaction Feature Pyramid Network (CARIFPN), which significantly enhances small object feature detection while reducing redundant network structures. Secondly, we apply a new downsampling convolution for small object feature extraction, called Space-to-Depth for Dilation-wise Residual Convolution (S2DResConv), in the model\u2019s backbone. This module effectively eliminates information loss caused by strided convolution or pooling operations and facilitates the capture of multi-scale context. Finally, we integrate a simple, parameter-free attention module (SimAM) with C3k2 to form Flexible SimAM (FlexSimAM), which is applied throughout the entire model. This improved module not only reduces the model\u2019s complexity but also enables efficient enhancement of small object features in complex scenarios. Experimental results demonstrate that on the VisDrone-DET2019 dataset, our model improves mAP@0.5 by 7.8% on the validation set (reaching 46.0%) and by 5.9% on the test set (increasing to 37.3%) compared to the baseline YOLO11s, while reducing model parameters by 55.3%. Similarly, it achieves a 7.2% improvement on the TinyPerson dataset and a 3.0% increase on UAVDT-DET. Deployment on the NVIDIA Jetson Orin NX SUPER platform shows that our model achieves 33 FPS, which is 21.4% lower than YOLO11s, confirming its feasibility for real-time onboard UAV applications.<\/jats:p>","DOI":"10.3390\/jimaging12020069","type":"journal-article","created":{"date-parts":[[2026,2,6]],"date-time":"2026-02-06T13:33:50Z","timestamp":1770384830000},"page":"69","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":6,"title":["YOLO11s-UAV: An Advanced Algorithm for Small Object Detection in UAV Aerial Imagery"],"prefix":"10.3390","volume":"12","author":[{"ORCID":"https:\/\/orcid.org\/0009-0004-5922-4364","authenticated-orcid":false,"given":"Qi","family":"Mi","sequence":"first","affiliation":[{"name":"College of Mechanical and Electrical Engineering, Fujian Agriculture and Forestry University, Fuzhou 350108, China"},{"name":"Quanzhou Institute of Equipment Manufacturing, Haixi Institutes, Chinese Academy of Sciences, Quanzhou 362216, China"},{"name":"Fujian Institute of Research on the Structure of Matter, Chinese Academy of Sciences, Fuzhou 350025, China"},{"name":"Fujian College, University of Chinese Academy of Sciences, Fuzhou 350025, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-7197-5919","authenticated-orcid":false,"given":"Jianshu","family":"Chao","sequence":"additional","affiliation":[{"name":"Quanzhou Institute of Equipment Manufacturing, Haixi Institutes, Chinese Academy of Sciences, Quanzhou 362216, China"},{"name":"Fujian Institute of Research on the Structure of Matter, Chinese Academy of Sciences, Fuzhou 350025, China"},{"name":"Fujian College, University of Chinese Academy of Sciences, Fuzhou 350025, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0009-0000-2993-450X","authenticated-orcid":false,"given":"Anqi","family":"Chen","sequence":"additional","affiliation":[{"name":"College of Mechanical and Electrical Engineering, Fujian Agriculture and Forestry University, Fuzhou 350108, China"},{"name":"Quanzhou Institute of Equipment Manufacturing, Haixi Institutes, Chinese Academy of Sciences, Quanzhou 362216, China"},{"name":"Fujian Institute of Research on the Structure of Matter, Chinese Academy of Sciences, Fuzhou 350025, China"},{"name":"Fujian College, University of Chinese Academy of Sciences, Fuzhou 350025, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0009-0007-0991-9784","authenticated-orcid":false,"given":"Kaiyuan","family":"Zhang","sequence":"additional","affiliation":[{"name":"Quanzhou Institute of Equipment Manufacturing, Haixi Institutes, Chinese Academy of Sciences, Quanzhou 362216, China"},{"name":"Fujian Institute of Research on the Structure of Matter, Chinese Academy of Sciences, Fuzhou 350025, China"},{"name":"Fujian College, University of Chinese Academy of Sciences, Fuzhou 350025, China"},{"name":"School of Advanced Manufacturing, Fuzhou University, Quanzhou 362251, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0009-0008-2179-6745","authenticated-orcid":false,"given":"Jiahua","family":"Lai","sequence":"additional","affiliation":[{"name":"Quanzhou Institute of Equipment Manufacturing, Haixi Institutes, Chinese Academy of Sciences, Quanzhou 362216, China"},{"name":"Fujian Institute of Research on the Structure of Matter, Chinese Academy of Sciences, Fuzhou 350025, China"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2026,2,6]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","unstructured":"Yao, H., Qin, R., and Chen, X. 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