To address the issues of low accuracy in manual observation and slow detection by radar in airport bird detection, this paper designs a lightweight bird detection network named MFE-YOLOv8. This network is based on the YOLOv8 framework, with the main body part featuring an MF module replacing the original C2f module to enhance the network's feature extraction capability. An EMA mechanism is added to increase the focus on bird targets, and the Focal-Modulation module is introduced to reduce background interference. Additionally, a DCSlideLoss is designed during the supervised network training process to alleviate the imbalance of samples. Finally, the real-time detection performance is verifie... More >