{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,8,23]],"date-time":"2026-08-23T20:21:28Z","timestamp":1787516488667,"version":"build-2736575974"},"reference-count":84,"publisher":"Elsevier BV","license":[{"start":{"date-parts":[[2027,1,1]],"date-time":"2027-01-01T00:00:00Z","timestamp":1798761600000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.elsevier.com\/tdm\/userlicense\/1.0\/"},{"start":{"date-parts":[[2027,1,1]],"date-time":"2027-01-01T00:00:00Z","timestamp":1798761600000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.elsevier.com\/legal\/tdmrep-license"},{"start":{"date-parts":[[2027,1,1]],"date-time":"2027-01-01T00:00:00Z","timestamp":1798761600000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-017"},{"start":{"date-parts":[[2027,1,1]],"date-time":"2027-01-01T00:00:00Z","timestamp":1798761600000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-037"},{"start":{"date-parts":[[2027,1,1]],"date-time":"2027-01-01T00:00:00Z","timestamp":1798761600000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-012"},{"start":{"date-parts":[[2027,1,1]],"date-time":"2027-01-01T00:00:00Z","timestamp":1798761600000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2027,1,1]],"date-time":"2027-01-01T00:00:00Z","timestamp":1798761600000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-004"}],"funder":[{"DOI":"10.13039\/501100012166","name":"National Key Research and Development Program of China","doi-asserted-by":"publisher","award":["2024YFB4708700"],"award-info":[{"award-number":["2024YFB4708700"]}],"id":[{"id":"10.13039\/501100012166","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100002855","name":"Ministry of Science and Technology of the People&apos;s Republic of China","doi-asserted-by":"publisher","id":[{"id":"10.13039\/501100002855","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["U24A20262"],"award-info":[{"award-number":["U24A20262"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["elsevier.com","sciencedirect.com"],"crossmark-restriction":true},"short-container-title":["Expert Systems with Applications"],"published-print":{"date-parts":[[2027,1]]},"DOI":"10.1016\/j.eswa.2026.134003","type":"journal-article","created":{"date-parts":[[2026,8,17]],"date-time":"2026-08-17T15:42:41Z","timestamp":1786981361000},"page":"134003","update-policy":"https:\/\/doi.org\/10.1016\/elsevier_cm_policy","source":"Crossref","is-referenced-by-count":0,"special_numbering":"PC","title":["WACFN: Tackling dense and tiny object detection in aerial imagery via weighted aggregation and cross-scale fusion"],"prefix":"10.1016","volume":"333","author":[{"ORCID":"https:\/\/orcid.org\/0009-0001-5074-5997","authenticated-orcid":false,"given":"Chao","family":"Chang","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0009-0009-3360-1199","authenticated-orcid":false,"given":"Xiuyu","family":"Wang","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0009-0003-7915-4941","authenticated-orcid":false,"given":"Zihan","family":"Guo","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0009-0009-9827-5726","authenticated-orcid":false,"given":"Xingyu","family":"Mu","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-9814-9521","authenticated-orcid":false,"given":"Xincheng","family":"Tian","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-3308-870X","authenticated-orcid":false,"given":"Lelai","family":"Zhou","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"78","reference":[{"key":"10.1016\/j.eswa.2026.134003_bib0001","series-title":"2018\u202fIEEE\/CVF Conference on computer vision and pattern recognition","first-page":"6154","article-title":"Cascade r-CNN: Delving into high quality object detection","author":"Cai","year":"2018"},{"issue":"7","key":"10.1016\/j.eswa.2026.134003_bib0002","doi-asserted-by":"crossref","first-page":"554","DOI":"10.1007\/s11760-025-04013-x","article-title":"Rethinking the structural similarity in small object detection","volume":"19","author":"Chai","year":"2025","journal-title":"Signal, Image and Video Processing"},{"key":"10.1016\/j.eswa.2026.134003_bib0003","first-page":"1","article-title":"IAMF-YOLO: Metal surface defect detection based on improved yolov8","volume":"74","author":"Chao","year":"2025","journal-title":"IEEE Transactions on Instrumentation and Measurement"},{"key":"10.1016\/j.eswa.2026.134003_bib0004","doi-asserted-by":"crossref","DOI":"10.1016\/j.eswa.2025.129710","article-title":"Freq-DETR: Frequency-aware transformer for real-time small object detection in unmanned aerial vehicle imagery","volume":"298","author":"Chen","year":"2026","journal-title":"Expert Systems with Applications"},{"key":"10.1016\/j.eswa.2026.134003_bib0005","article-title":"Enhanced semantic feature pyramid network for small object detection","volume":"113","author":"Chen","year":"2023","journal-title":"Signal Processing: Image Communication"},{"issue":"3","key":"10.1016\/j.eswa.2026.134003_bib0006","doi-asserted-by":"crossref","first-page":"431","DOI":"10.1109\/LGRS.2020.2975541","article-title":"Cross-scale feature fusion for object detection in optical remote sensing images","volume":"18","author":"Cheng","year":"2021","journal-title":"IEEE Geoscience and Remote Sensing Letters"},{"issue":"10","key":"10.1016\/j.eswa.2026.134003_bib0007","doi-asserted-by":"crossref","first-page":"8984","DOI":"10.1109\/TCSVT.2022.3232688","article-title":"Tiny object detection via regional cross self-attention network","volume":"34","author":"Cheng","year":"2024","journal-title":"IEEE Transactions on Circuits and Systems for Video Technology"},{"key":"10.1016\/j.eswa.2026.134003_bib0008","first-page":"1","article-title":"Cross-layer feature pyramid transformer for small object detection in aerial images","volume":"63","author":"Du","year":"2025","journal-title":"IEEE Transactions on Geoscience and Remote Sensing"},{"issue":"6","key":"10.1016\/j.eswa.2026.134003_bib0009","doi-asserted-by":"crossref","first-page":"1639","DOI":"10.1109\/TCSVT.2019.2906246","article-title":"Detecting small objects using a channel-aware deconvolutional network","volume":"30","author":"Duan","year":"2020","journal-title":"IEEE Transactions on Circuits and Systems for Video Technology"},{"key":"10.1016\/j.eswa.2026.134003_bib0010","first-page":"1","article-title":"Weighted learnable recursive aggregation network for visible remote sensing image detection","volume":"63","author":"Duan","year":"2025","journal-title":"IEEE Transactions on Geoscience and Remote Sensing"},{"key":"10.1016\/j.eswa.2026.134003_bib0011","series-title":"2021\u202fIEEE\/CVF International conference on computer vision (ICCV)","first-page":"3490","article-title":"TOOD: Task-aligned one-stage object detection","author":"Feng","year":"2021"},{"key":"10.1016\/j.eswa.2026.134003_bib0012","doi-asserted-by":"crossref","unstructured":"Gao, B., Tong, J., Chen, X., Yu, H., & Li, Z. (2025). DFIR-DETR: Frequency domain enhancement and dynamic feature aggregation for cross-scene small object detection. arXiv: 2512.07078.","DOI":"10.1016\/j.neunet.2026.109256"},{"key":"10.1016\/j.eswa.2026.134003_bib0013","unstructured":"Gevorgyan, Z. (2022). SIoU loss: More powerful learning for bounding box regression. arXiv: 2205.12740."},{"key":"10.1016\/j.eswa.2026.134003_bib0014","first-page":"1","article-title":"Crater-DETR: A novel transformer network for crater detection based on dense supervision and multiscale fusion","volume":"62","author":"Guo","year":"2024","journal-title":"IEEE Transactions on Geoscience and Remote Sensing"},{"key":"10.1016\/j.eswa.2026.134003_bib0015","doi-asserted-by":"crossref","DOI":"10.1016\/j.engappai.2025.111730","article-title":"An enhanced framework for small object detection with middle-order interaction and adaptive cross-scale aggregation","volume":"159","author":"Guo","year":"2025","journal-title":"Engineering Applications of Artificial Intelligence"},{"key":"10.1016\/j.eswa.2026.134003_bib0016","series-title":"2016\u202fIEEE Conference on computer vision and pattern recognition (CVPR)","first-page":"770","article-title":"Deep residual learning for image recognition","author":"He","year":"2016"},{"key":"10.1016\/j.eswa.2026.134003_bib0017","doi-asserted-by":"crossref","DOI":"10.1016\/j.eswa.2025.128459","article-title":"MFEL-YOLO for small object detection in UAV aerial images","volume":"291","author":"Hou","year":"2025","journal-title":"Expert Systems with Applications"},{"key":"10.1016\/j.eswa.2026.134003_bib0018","unstructured":"Howard, A. G., Zhu, M., Chen, B., Kalenichenko, D., Wang, W., Weyand, T., Andreetto, M., & Adam, H. (2017). MobileNets: Efficient convolutional neural networks for mobile vision applications. arXiv: 1704.04861."},{"key":"10.1016\/j.eswa.2026.134003_bib0019","series-title":"2018\u202fIEEE\/CVF Conference on computer vision and pattern recognition","first-page":"7132","article-title":"Squeeze-and-excitation networks","author":"Hu","year":"2018"},{"key":"10.1016\/j.eswa.2026.134003_bib0020","first-page":"1","article-title":"CSFPR-RTDETR: Real-time small object detection network for uav images based on cross-spatial-frequency domain and position relation","volume":"63","author":"Hu","year":"2025","journal-title":"IEEE Transactions on Geoscience and Remote Sensing"},{"key":"10.1016\/j.eswa.2026.134003_bib0021","unstructured":"Jiang, X., Zhang, W., & Mao, X. (2025). RS-TinyNet: Stage-wise feature fusion network for detecting tiny objects in remote sensing images. arXiv: 2507.13120."},{"key":"10.1016\/j.eswa.2026.134003_bib0022","unstructured":"Jiang, Y., Tan, Z., Wang, J., Sun, X., Lin, M., & Li, H. (2022). GirafFedet: A heavy-neck paradigm for object detection. arXiv: 2202.04256."},{"key":"10.1016\/j.eswa.2026.134003_bib0023","unstructured":"Jocher, G. (2020). Ultralytics YOLOv5. Computer software, Version 7.0. https:\/\/doi.org\/10.5281\/zenodo.3908559."},{"key":"10.1016\/j.eswa.2026.134003_bib0024","unstructured":"Jocher, G., Chaurasia, A., & Qiu, J. (2023). Ultralytics YOLOv8. Computer software.https:\/\/github.com\/ultralytics\/ultralytics."},{"key":"10.1016\/j.eswa.2026.134003_bib0025","unstructured":"Khanam, R., & Hussain, M. (2024). YOLOv11: An overview of the key architectural enhancements. arXiv: 2410.17725."},{"issue":"11","key":"10.1016\/j.eswa.2026.134003_bib0026","doi-asserted-by":"crossref","DOI":"10.1016\/j.asej.2024.103046","article-title":"Optimizing the loss function for bounding box regression through scale smoothing","volume":"15","author":"Lei","year":"2024","journal-title":"Ain Shams Engineering Journal"},{"key":"10.1016\/j.eswa.2026.134003_bib0027","unstructured":"Li, J., Zhu, H., Yang, W., Zhang, J., Xu, F., Zhang, H., & Xia, G.-S. (2026). UHR-DETR: Efficient end-to-end small object detection for ultra-high-resolution remote sensing imagery. arXiv: 2604.21435."},{"issue":"9","key":"10.1016\/j.eswa.2026.134003_bib0028","doi-asserted-by":"crossref","first-page":"8053","DOI":"10.1109\/TCSVT.2024.3385121","article-title":"Toward high-accuracy and real-time two-stage small object detection on FPGA","volume":"34","author":"Li","year":"2024","journal-title":"IEEE Transactions on Circuits and Systems for Video Technology"},{"key":"10.1016\/j.eswa.2026.134003_bib0029","series-title":"Proceedings of the IEEE\/CVF Conference on computer vision and pattern recognition","first-page":"11632","article-title":"Generalized focal loss v2: Learning reliable localization quality estimation for dense object detection","author":"Li","year":"2021"},{"key":"10.1016\/j.eswa.2026.134003_bib0030","series-title":"2019\u202fIEEE\/CVF International conference on computer vision (ICCV)","first-page":"6053","article-title":"Scale-aware trident networks for object detection","author":"Li","year":"2019"},{"key":"10.1016\/j.eswa.2026.134003_bib0031","doi-asserted-by":"crossref","first-page":"3047","DOI":"10.1109\/TIP.2024.3391011","article-title":"Learning contrast-enhanced shape-biased representations for infrared small target detection","volume":"33","author":"Lin","year":"2024","journal-title":"IEEE Transactions on Image Processing"},{"key":"10.1016\/j.eswa.2026.134003_bib0032","series-title":"2017\u202fIEEE Conference on computer vision and pattern recognition (CVPR)","first-page":"936","article-title":"Feature pyramid networks for object detection","author":"Lin","year":"2017"},{"issue":"2","key":"10.1016\/j.eswa.2026.134003_bib0033","doi-asserted-by":"crossref","first-page":"318","DOI":"10.1109\/TPAMI.2018.2858826","article-title":"Focal loss for dense object detection","volume":"42","author":"Lin","year":"2020","journal-title":"IEEE Transactions on Pattern Analysis and Machine Intelligence"},{"key":"10.1016\/j.eswa.2026.134003_bib0034","series-title":"European conference on computer vision","first-page":"740","article-title":"Microsoft coco: Common objects in context","author":"Lin","year":"2014"},{"key":"10.1016\/j.eswa.2026.134003_bib0035","doi-asserted-by":"crossref","first-page":"276","DOI":"10.1016\/j.neunet.2023.11.041","article-title":"Powerful-IoU: More straightforward and faster bounding box regression loss with a nonmonotonic focusing mechanism","volume":"170","author":"Liu","year":"2024","journal-title":"Neural Networks"},{"key":"10.1016\/j.eswa.2026.134003_bib0036","series-title":"2018\u202fIEEE\/CVF Conference on computer vision and pattern recognition","first-page":"8759","article-title":"Path aggregation network for instance segmentation","author":"Liu","year":"2018"},{"key":"10.1016\/j.eswa.2026.134003_bib0037","series-title":"2023 42nd Chinese control conference (CCC)","first-page":"7507","article-title":"EdgeYOLO: An edge-real-time object detector","author":"Liu","year":"2023"},{"key":"10.1016\/j.eswa.2026.134003_bib0038","unstructured":"Liu, Y., Shao, Z., & Hoffmann, N. (2021). Global attention mechanism: Retain information to enhance channel-spatial interactions. arXiv: 2112.05561."},{"key":"10.1016\/j.eswa.2026.134003_bib0039","series-title":"Proceedings of the AAAI conference on artificial intelligence","first-page":"11685","article-title":"Training-time-friendly network for real-time object detection","volume":"vol. 34","author":"Liu","year":"2020"},{"issue":"12","key":"10.1016\/j.eswa.2026.134003_bib0040","doi-asserted-by":"crossref","first-page":"1997","DOI":"10.3390\/rs17121997","article-title":"HSF-DETR: Hyper scale fusion detection transformer for multi-perspective uav object detection","volume":"17","author":"Mao","year":"2025","journal-title":"Remote Sensing"},{"key":"10.1016\/j.eswa.2026.134003_bib0041","first-page":"1","article-title":"AMFLW-YOLO: A lightweight network for remote sensing image detection based on attention mechanism and multiscale feature fusion","volume":"61","author":"Peng","year":"2023","journal-title":"IEEE Transactions on Geoscience and Remote Sensing"},{"key":"10.1016\/j.eswa.2026.134003_bib0042","series-title":"Proceedings of the IEEE\/CVF Conference on computer vision and pattern recognition","first-page":"10213","article-title":"Detectors: Detecting objects with recursive feature pyramid and switchable atrous convolution","author":"Qiao","year":"2021"},{"issue":"6","key":"10.1016\/j.eswa.2026.134003_bib0043","doi-asserted-by":"crossref","first-page":"1137","DOI":"10.1109\/TPAMI.2016.2577031","article-title":"Faster r-CNN: Towards real-time object detection with region proposal networks","volume":"39","author":"Ren","year":"2016","journal-title":"IEEE Transactions on Pattern Analysis and Machine Intelligence"},{"key":"10.1016\/j.eswa.2026.134003_bib0044","series-title":"2019\u202fIEEE\/CVF Conference on computer vision and pattern recognition (CVPR)","first-page":"658","article-title":"Generalized intersection over union: A metric and a loss for bounding box regression","author":"Rezatofighi","year":"2019"},{"key":"10.1016\/j.eswa.2026.134003_bib0045","series-title":"2025\u202fIEEE\/CVF Conference on computer vision and pattern recognition (CVPR)","first-page":"4713","article-title":"Set: Spectral enhancement for tiny object detection","author":"Sun","year":"2025"},{"key":"10.1016\/j.eswa.2026.134003_bib0046","article-title":"Noise-robust tiny object localization with flows","author":"Sun","year":"2026","journal-title":"Pattern Recognition"},{"key":"10.1016\/j.eswa.2026.134003_bib0047","series-title":"2020\u202fIEEE\/CVF Conference on computer vision and pattern recognition (CVPR)","first-page":"10778","article-title":"EfficientDet: Scalable and efficient object detection","author":"Tan","year":"2020"},{"key":"10.1016\/j.eswa.2026.134003_bib0048","series-title":"2019\u202fIEEE\/CVF International conference on computer vision (ICCV)","first-page":"9626","article-title":"Fcos: Fully convolutional one-stage object detection","author":"Tian","year":"2019"},{"key":"10.1016\/j.eswa.2026.134003_bib0049","doi-asserted-by":"crossref","unstructured":"Wang, A., Chen, H., Liu, L., Chen, K., Lin, Z., Han, J., & Ding, G. (2024a). YOLOv10: Real-time end-to-end object detection. arXiv: 2405.14458.","DOI":"10.52202\/079017-3429"},{"issue":"1","key":"10.1016\/j.eswa.2026.134003_bib0050","article-title":"CF-YOLO for small target detection in drone imagery based on yolov11 algorithm","volume":"15","author":"Wang","year":"2025","journal-title":"Scientific Reports"},{"key":"10.1016\/j.eswa.2026.134003_bib0051","doi-asserted-by":"crossref","first-page":"51094","DOI":"10.52202\/075280-2224","article-title":"Gold-YOLO: Efficient object detector via gather-and-distribute mechanism","volume":"36","author":"Wang","year":"2023","journal-title":"Advances in Neural Information Processing Systems"},{"key":"10.1016\/j.eswa.2026.134003_bib0052","series-title":"European conference on computer vision","first-page":"1","article-title":"YOLOv9: Learning what you want to learn using programmable gradient information","author":"Wang","year":"2025"},{"key":"10.1016\/j.eswa.2026.134003_bib0053","series-title":"2024\u202fIEEE\/CVF Conference on computer vision and pattern recognition (CVPR)","first-page":"16520","article-title":"CrossKD: Cross-head knowledge distillation for object detection","author":"Wang","year":"2024"},{"issue":"10","key":"10.1016\/j.eswa.2026.134003_bib0054","doi-asserted-by":"crossref","first-page":"3349","DOI":"10.1109\/TPAMI.2020.2983686","article-title":"Deep high-resolution representation learning for visual recognition","volume":"43","author":"Wang","year":"2021","journal-title":"IEEE Transactions on Pattern Analysis and Machine Intelligence"},{"key":"10.1016\/j.eswa.2026.134003_bib0055","series-title":"2020 25th International conference on pattern recognition (ICPR)","first-page":"3791","article-title":"Tiny object detection in aerial images","author":"Wang","year":"2021"},{"key":"10.1016\/j.eswa.2026.134003_bib0056","doi-asserted-by":"crossref","DOI":"10.1016\/j.jvcir.2023.103752","article-title":"FE-YOLOv5: Feature enhancement network based on yolov5 for small object detection","volume":"90","author":"Wang","year":"2023","journal-title":"Journal of Visual Communication and Image Representation"},{"key":"10.1016\/j.eswa.2026.134003_bib0057","series-title":"2020\u202fIEEE\/CVF Conference on computer vision and pattern recognition (CVPR)","first-page":"11531","article-title":"ECA-Net: Efficient channel attention for deep convolutional neural networks","author":"Wang","year":"2020"},{"key":"10.1016\/j.eswa.2026.134003_bib0058","unstructured":"Wen, Z., Yang, Z., Bao, X., Zhang, L., Xiang, X., Li, W., & Liu, Y. (2026). D3R-DETR: DETR with dual-domain density refinement for tiny object detection in aerial images. arXiv: 2601.02747."},{"key":"10.1016\/j.eswa.2026.134003_bib0059","series-title":"Proceedings of the European conference on computer vision (ECCV)","first-page":"3","article-title":"Cbam: Convolutional block attention module","author":"Woo","year":"2018"},{"key":"10.1016\/j.eswa.2026.134003_bib0060","first-page":"1","article-title":"FSANet: Feature-and-spatial-aligned network for tiny object detection in remote sensing images","volume":"60","author":"Wu","year":"2022","journal-title":"IEEE Transactions on Geoscience and Remote Sensing"},{"key":"10.1016\/j.eswa.2026.134003_bib0061","doi-asserted-by":"crossref","first-page":"364","DOI":"10.1109\/TIP.2022.3228497","article-title":"Uiu-net: U-net in u-net for infrared small object detection","volume":"32","author":"Wu","year":"2022","journal-title":"IEEE Transactions on Image Processing"},{"key":"10.1016\/j.eswa.2026.134003_bib0062","series-title":"2018\u202fIEEE\/CVF Conference on computer vision and pattern recognition","first-page":"3974","article-title":"Dota: A large-scale dataset for object detection in aerial images","author":"Xia","year":"2018"},{"key":"10.1016\/j.eswa.2026.134003_bib0063","doi-asserted-by":"crossref","unstructured":"Xia, Y., Liu, C., Xiang, T., & Tu, Z. (2026). Efsi-detr: Efficient frequency-semantic integration for real-time small object detection in uav imagery. arXiv: 2601.18597.","DOI":"10.1109\/TMM.2026.3716762"},{"key":"10.1016\/j.eswa.2026.134003_bib0064","doi-asserted-by":"crossref","DOI":"10.1016\/j.eswa.2025.129346","article-title":"Density-guided two-stage small object detection in UAV images","volume":"297","author":"Xie","year":"2026","journal-title":"Expert Systems with Applications"},{"key":"10.1016\/j.eswa.2026.134003_bib0065","series-title":"2023\u202fIEEE\/CVF Conference on computer vision and pattern recognition (CVPR)","first-page":"7318","article-title":"Dynamic coarse-to-fine learning for oriented tiny object detection","author":"Xu","year":"2023"},{"key":"10.1016\/j.eswa.2026.134003_bib0066","series-title":"European conference on computer vision","first-page":"526","article-title":"Rfla: Gaussian receptive field based label assignment for tiny object detection","author":"Xu","year":"2022"},{"key":"10.1016\/j.eswa.2026.134003_bib0067","series-title":"2021\u202fIEEE\/CVF Conference on computer vision and pattern recognition workshops (CVPRW)","first-page":"1192","article-title":"Dot distance for tiny object detection in aerial images","author":"Xu","year":"2021"},{"key":"10.1016\/j.eswa.2026.134003_bib0068","doi-asserted-by":"crossref","DOI":"10.1016\/j.cviu.2025.104409","article-title":"HCTD: A CNN-transformer hybrid for precise object detection in uav aerial imagery","volume":"259","author":"Xue","year":"2025","journal-title":"Computer Vision and Image Understanding"},{"key":"10.1016\/j.eswa.2026.134003_bib0069","series-title":"2023\u202fIEEE\/CVF International conference on computer vision (ICCV)","first-page":"17129","article-title":"Bridging cross-task protocol inconsistency for distillation in dense object detection","author":"Yang","year":"2023"},{"key":"10.1016\/j.eswa.2026.134003_bib0070","series-title":"2019\u202fIEEE\/CVF International conference on computer vision (ICCV)","first-page":"9656","article-title":"Reppoints: Point set representation for object detection","author":"Yang","year":"2019"},{"key":"10.1016\/j.eswa.2026.134003_bib0071","first-page":"1","article-title":"Domain-invariant progressive knowledge distillation for UAV-based object detection","volume":"22","author":"Yao","year":"2025","journal-title":"IEEE Geoscience and Remote Sensing Letters"},{"key":"10.1016\/j.eswa.2026.134003_bib0072","unstructured":"Zhang, H., Li, F., Liu, S., Zhang, L., Su, H., Zhu, J., Ni, L. M., & Shum, H.-Y. (2022a). Dino: Detr with improved denoising anchor boxes for end-to-end object detection. arXiv: 2203.03605."},{"key":"10.1016\/j.eswa.2026.134003_bib0073","unstructured":"Zhang, H., & Zhang, S. (2023). Shape-iou: More accurate metric considering bounding box shape and scale. arXiv: 2312.17663."},{"key":"10.1016\/j.eswa.2026.134003_bib0074","series-title":"International conference on multimedia modeling","first-page":"394","article-title":"MKSNet: Advanced small object detection in remote sensing imagery with multi-kernel and dual attention mechanisms","author":"Zhang","year":"2024"},{"key":"10.1016\/j.eswa.2026.134003_bib0075","series-title":"2020\u202fIEEE\/CVF Conference on computer vision and pattern recognition (CVPR)","first-page":"9756","article-title":"Bridging the gap between anchor-based and anchor-free detection via adaptive training sample selection","author":"Zhang","year":"2020"},{"key":"10.1016\/j.eswa.2026.134003_bib0076","doi-asserted-by":"crossref","first-page":"146","DOI":"10.1016\/j.neucom.2022.07.042","article-title":"Focal and efficient IOU loss for accurate bounding box regression","volume":"506","author":"Zhang","year":"2022","journal-title":"Neurocomputing"},{"key":"10.1016\/j.eswa.2026.134003_bib0077","series-title":"2024\u202fIEEE\/CVF Conference on computer vision and pattern recognition (CVPR)","first-page":"16965","article-title":"Detrs beat yolos on real-time object detection","author":"Zhao","year":"2024"},{"key":"10.1016\/j.eswa.2026.134003_bib0078","first-page":"1","article-title":"Dense tiny object detection: A scene context guided approach and a unified benchmark","volume":"62","author":"Zhao","year":"2024","journal-title":"IEEE Transactions on Geoscience and Remote Sensing"},{"key":"10.1016\/j.eswa.2026.134003_bib0079","series-title":"Proceedings of the AAAI conference on artificial intelligence","first-page":"12993","article-title":"Distance-iou loss: Faster and better learning for bounding box regression","volume":"vol. 34","author":"Zheng","year":"2020"},{"key":"10.1016\/j.eswa.2026.134003_bib0080","unstructured":"Zhou, X., Wang, D., & Kr\u00e4henb\u00fchl, P. (2019). Objects as points. arXiv: 1904.07850."},{"key":"10.1016\/j.eswa.2026.134003_bib0081","unstructured":"Zhu, B., Wang, J., Jiang, Z., Zong, F., Liu, S., Li, Z., & Sun, J. (2020a). Autoassign: Differentiable label assignment for dense object detection. arXiv: 2007.03496."},{"issue":"11","key":"10.1016\/j.eswa.2026.134003_bib0082","doi-asserted-by":"crossref","first-page":"7380","DOI":"10.1109\/TPAMI.2021.3119563","article-title":"Detection and tracking meet drones challenge","volume":"44","author":"Zhu","year":"2021","journal-title":"IEEE Transactions on Pattern Analysis and Machine Intelligence"},{"key":"10.1016\/j.eswa.2026.134003_bib0083","unstructured":"Zhu, X., Su, W., Lu, L., Li, B., Wang, X., & Dai, J. (2020b). Deformable detr: Deformable transformers for end-to-end object detection. arXiv: 2010.04159."},{"issue":"10","key":"10.1016\/j.eswa.2026.134003_bib0084","doi-asserted-by":"crossref","first-page":"10011","DOI":"10.1109\/TCSVT.2024.3402097","article-title":"Small object detection method based on global multi-level perception and dynamic region aggregation","volume":"34","author":"Zhu","year":"2024","journal-title":"IEEE Transactions on Circuits and Systems for Video Technology"}],"container-title":["Expert Systems with Applications"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S095741742602909X?httpAccept=text\/xml","content-type":"text\/xml","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S095741742602909X?httpAccept=text\/plain","content-type":"text\/plain","content-version":"vor","intended-application":"text-mining"}],"deposited":{"date-parts":[[2026,8,23]],"date-time":"2026-08-23T19:38:21Z","timestamp":1787513901000},"score":1,"resource":{"primary":{"URL":"https:\/\/linkinghub.elsevier.com\/retrieve\/pii\/S095741742602909X"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2027,1]]},"references-count":84,"alternative-id":["S095741742602909X"],"URL":"https:\/\/doi.org\/10.1016\/j.eswa.2026.134003","relation":{},"ISSN":["0957-4174"],"issn-type":[{"value":"0957-4174","type":"print"}],"subject":[],"published":{"date-parts":[[2027,1]]},"assertion":[{"value":"Elsevier","name":"publisher","label":"This article is maintained by"},{"value":"WACFN: Tackling dense and tiny object detection in aerial imagery via weighted aggregation and cross-scale fusion","name":"articletitle","label":"Article Title"},{"value":"Expert Systems with Applications","name":"journaltitle","label":"Journal Title"},{"value":"https:\/\/doi.org\/10.1016\/j.eswa.2026.134003","name":"articlelink","label":"CrossRef DOI link to publisher maintained version"},{"value":"article","name":"content_type","label":"Content Type"},{"value":"\u00a9 2026 Elsevier Ltd. All rights are reserved, including those for text and data mining, AI training, and similar technologies.","name":"copyright","label":"Copyright"}],"article-number":"134003"}}