Small object detection algorithm in UAV aerial images based on improved YOLO11
Image Processing|更新时间:2025-06-05
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Small object detection algorithm in UAV aerial images based on improved YOLO11
“In the field of small object detection in drone aerial images, the ACFI-YOLO11 algorithm significantly improves detection performance through lightweight design and cross layer feature interaction, providing an efficient and practical solution for solving small object detection problems.”
Chinese Journal of Liquid Crystals and DisplaysVol. 40, Issue 6, Pages: 915-930(2025)
作者机构:
浙江大学 电气工程学院, 浙江 杭州 310027
作者简介:
基金信息:
“Jianbing” Science and Technology Plan of Zhejiang Province(2023C01129)
ZHANG Zhihao, LI Xiaorun, CHEN Shuhan. Small object detection algorithm in UAV aerial images based on improved YOLO11[J]. Chinese journal of liquid crystals and displays, 2025, 40(6): 915-930.
DOI:
ZHANG Zhihao, LI Xiaorun, CHEN Shuhan. Small object detection algorithm in UAV aerial images based on improved YOLO11[J]. Chinese journal of liquid crystals and displays, 2025, 40(6): 915-930. DOI: 10.37188/CJLCD.2025-0010. CSTR: 32172.14.CJLCD.2025-0010.
Small object detection algorithm in UAV aerial images based on improved YOLO11