[2] Seo T, Jeon Y, Park C et al. Survey on glass and façade-cleaning robots: climbing mechanisms, cleaning methods, and applications[J]. International Journal of Precision Engineering and Manufacturing-Green Technology, 6, 367-376(2019).

[3] Zhang H X, Zhang J W, Wang W et al. A series of pneumatic glass-wall cleaning robots for high-rise buildings[J]. Industrial Robot, 34, 150-160(2007).

[4] Deng Z P, Liu H, Tu J L et al. SGS-YOLO: method for detecting dress code violations by airport security personnel[J]. Laser & Optoelectronics Progress, 62, 0637010(2025).

[5] Luo Y X, Liu C L, Li X. GELAN-YOLOv8 algorithm for contraband detection in X-ray image[J]. Laser & Optoelectronics Progress, 62, 0237008(2025).

[6] Jiang P Y, Ergu D J, Liu F Y et al. A review of YOLO algorithm developments[J]. Procedia Computer Science, 199, 1066-1073(2022).

[7] Bai F, Ma Q L, Zhao M. AC-YOLO for aerial pavement crack detection[J]. Computer Engineering and Applications, 61, 153-164(2025).

[8] Hu H J, Qin Y F, Xu H et al. An improved YOLOv8 object detection algorithm for UAV aerial images[J]. Computer Science, 52, 202-211(2025).

[9] Bochkovskiy A, Wang C Y, Liao H Y M. YOLOv4: optimal speed and accuracy of object detection[EB/OL]. https://arxiv.org/abs/2004.10934v1

[10] Dang H S, Gao W R, Meng R C et al. Target detect algorithm of lightweight in aerial images based on multi-scale feature fusion[J]. Electronic Measurement Technology, 47, 92-99(2024).

[11] Zuo J, Shi Y Y, Lu S H. Improved X-ray prohibited items detection method based on lightweight convolution blocks and SCAM[J]. Journal of Frontiers of Computer Science and Technology, 19, 1598-1610(2025).

[12] Liu W Z, Lu H, Fu H T et al. Learning to upsample by learning to sample[C], 6004-6014(2023).

[13] Shi W Z, Caballero J, Huszár F et al. Real-time single image and video super-resolution using an efficient sub-pixel convolutional neural network[C], 1874-1883(2016).

[14] Cao Y, Xu J R, Lin S et al. GCNet: non-local networks meet squeeze-excitation networks and beyond[C], 1971-1980(2019).

[15] Liu Y, Li H F, Hu C et al. Learning to aggregate multi-scale context for instance segmentation in remote sensing images[J]. IEEE Transactions on Neural Networks and Learning Systems, 36, 595-609(2025).

[16] Zhang Y, Ye M, Zhu G Y et al. FFCA-YOLO for small object detection in remote sensing images[J]. IEEE Transactions on Geoscience and Remote Sensing, 62, 5611215(2024).

[17] Zheng Z H, Wang P, Liu W et al. Distance-IoU loss: faster and better learning for bounding box regression[J]. Proceedings of the AAAI Conference on Artificial Intelligence, 34, 12993-13000(2020).

[18] Gu Z C, Zhu K, You S T. YOLO-SSFS: a method combining SPD-conv/STDL/IM-FPN/SIoU for outdoor small target vehicle detection[J]. Electronics, 12, 3744(2023).

[19] Yu J H, Jiang Y N, Wang Z Y et al. UnitBox: an advanced object detection network[C], 516-520(2016).

[20] Du D W, Qi Y K, Yu H Y et al. The unmanned aerial vehicle benchmark: object detection and tracking[M]. Computer vision-ECCV 2018, 11214, 375-391(2018).

[21] Li K, Wan G, Cheng G et al. Object detection in optical remote sensing images: a survey and a new benchmark[J]. ISPRS Journal of Photogrammetry and Remote Sensing, 159, 296-307(2020).

[22] Chen J R, Kao S H, He H et al. Run, don’t walk: chasing higher FLOPS for faster neural networks[C], 12021-12031(2023).