Abstract: To improve the intelligence of machine mapping and the efficiency and quality of map point annotation configuration, a map point annotation configuration method based on deep learning is proposed in this paper. Firstly, the paper obtains the pictures from the published altases to construct the map point annotation data sets, and then uses the Convolutional Neural Network and the Dense Convolutional Neural Network model to carry out research from the two aspects of map annotation category recognition and character recognition based on TensorFlow and MXNet. Finally, the annotation position matching is performed according to the text recognition results, and the annotation configuration is performed in combination with the annotation categories, which realizes the combination of deep learning method and map point annotation configuration. The research method of this paper can realize the automatic configuration of map point annotation and effectively improve the efficiency of map annotation configuration.