input filtering

Input filtering aims to screen out unnecessary input data during the model inference process, thereby reducing data transmission and computational overhead. By optimizing the data processing workflow, input filtering can improve model runtime efficiency, reduce resource consumption, and enhance the overall performance and scalability of the system. Within a methodological framework, input filtering is one of the key technologies for achieving efficient model deployment.