The invention discloses a lightweight wireless gesture recognition method based on attention enhancement, and the method comprises the steps: designing a lightweight network model (AELite) based on attention enhancement, and combining a bidirectional gated loop unit network (BiGRU), a residual convolution block (Res-Conv1D) and a channel attention module (CAM) to fully extract gesture features, the gesture action can be effectively recognized under the condition that the model parameters and the model size are controlled. According to the wireless gesture recognition method disclosed by the invention, the design of a lightweight model is emphasized while the system performance is improved, so that the requirements of a vehicle-mounted scene are met.
本发明公开了一种基于注意力增强的轻量级无线手势识别方法,通过设计基于注意力增强的轻量化网络模型(AELite),结合双向门控循环单元网络(BiGRU)、残差卷积块(Res‑Conv1D)、通道注意力模块(CAM)来充分提取手势特征,在模型参数、模型大小得到控制的条件下能够有效识别手势动作。本发明的无线手势识别方法在提升系统性能的同时,注重轻量级模型的设计,以适应车载场景的需求。
Lightweight wireless gesture recognition method based on attention enhancement
一种基于注意力增强的轻量级无线手势识别方法
2024-12-17
Patent
Electronic Resource
Chinese
IPC: | G06N COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS , Rechnersysteme, basierend auf spezifischen Rechenmodellen / B60K Anordnung oder Einbau von Antriebseinheiten oder von Kraft- bzw. Drehmomentübertragungen in Fahrzeugen , ARRANGEMENT OR MOUNTING OF PROPULSION UNITS OR OF TRANSMISSIONS IN VEHICLES / G06F ELECTRIC DIGITAL DATA PROCESSING , Elektrische digitale Datenverarbeitung |
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