Research on Optimal Algorithm of Image-based Feature Extraction Network Model

In view of the current traditional two-dimensional target detection algorithm's difficulty in balancing accuracy and speed, the feature extraction network is optimized in terms of structure and complexity. The image collected by the vision sensor is used as input, and the optimal parameter combination is selected through experiments, And through the comparison experiment between the optimized network model designed in each optimization stage and the traditional model to determine the best parameter selection, and verify the algorithm. The experimental results show that the optimized network model can effectively improve the accuracy of target detection under the condition of unchanged model complexity.