Research on document detection and recognition based on deep learning

As an important technology to promote office automation, document detection and recognition can improve the efficiency of business processes and user experience, make enterprise business more intelligent, and have very broad application scenarios. In this paper, a document detection and recognition system based on DB detection model and CRNN recognition model is built to detect and recognize document images using 3.64 million samples from the image dataset intercepted by ICDARD 2015 and Chinese corpus, and display the document information in the corresponding table in real time. The test results show that the system effectively improves the model inference speed while ensuring the accuracy of document recognition and detection, and completes the document information entry efficiently and quickly.