AMS-Net: Lightweight Self-Attention Enhanced MobileNetV3 for Real-Time Multimedia Classification on Edge Devices
This paper proposes AMS-Net, a lightweight MobileNetV3-Small architecture enhanced with a novel Low-complexity Spatial Self-Attention Module and a dynamic transfer learning strategy, which achieves superior real-time classification accuracy and efficiency on resource-constrained edge devices.