To address the challenges of complex backgrounds and low accuracy in detecting tomato leaves, we propose an improved tomato leaf detection model, YOLOv5s-SPD, based on the YOLOv5 network, for identifying tomato leaf diseases. First, the SSConv module is introduced into the backbone network of the YOLOv5 algorithm, replacing the C3 module with the SSConv module to reduce feature redundancy in both spatial and channel dimensions, thus lowering the computational load of the model. Additionally, a PSA attention mechanism is incorporated to enhance the model's feature extraction capability for toma...
