Based on tensor splitting technique, a decentralized computing method of neural network model for electromagnetic object detection is introduced. In this method, different tensor splitting techniques are selected according to different hidden layers, and the weights are distributed to multiple distributed nodes losslessly. The simulation results on Raspberry PI show that this method can decompose and deploy the centralized detection model losslessly, and ensure the same accuracy as the original model. And when the original model is too heavy to be loaded into memory for calculation, this method can still complete the calculation properly.