Research on Rapid Extraction and Recognition Based on Depth Learning Method in Regional Nomination Mode

The advent of the large data era, the development of deep learning theory helps to create a good condition. Data mining generally refers to the process of automatically searching for information that has special relevance hidden from a large amount of data. Data mining is usually related to computer science and it is achieved through statistical, on-line analytical processing, information retrieval, machine learning, expert systems which is relying on past rule of thumb and pattern recognition. This paper introduces the background of the deep learning development, and it mainly discusses the self-encoding method in the depth learning, and implements the simulation application from the self-coding method. The latest developments in information fusion technology make it possible to easily capture images of color and depth information in order to improve the image of object recognition. This paper also introduces a BP neural network model for feature learning and image classification. Our model achieves better artistic expression on standard image object sets, finally the results are more accurate and quicker in training and testing compared to other comparable architectures.