YFDM: YOLO for detecting Morse code

Abstract

AbstractWith the increasing complexity of the shortwave communication environment, the efficiency and accuracy of the manual detection of Morse code no longer meet actual needs. Therefore, this paper proposes a Morse code detection algorithm called YFDM. For the time–frequency image of the received signal, a combination module of deformable convolution and C3 is used to enhance the backbone network’s attention to the abstract semantics and location information of Morse code. GSConv and VOV-GSCSP modules are used to build a lightweight neck network. Finally, the confidence propagation cluster (CP-Cluster) algorithm is used to filter the detection frame. In an ablation experiment, the parameters and giga floating-point operations per second (GFLOPs) of YFDM were 5.961 M and 9.74 G, respectively, 15.11% and 38.9% less than those of YOLOv5. Moreover, when WIoUv1 was used as the loss function of the bounding box, the AP0.5:0.95 and frames per second (FPS) values of the algorithm reached the highest values, 0.68 and 72.4. The experimental results indicate that the algorithm can effectively reduce the weight of the model while ensuring the detection accuracy and inference speed.