Huang Zheng

TL;DR: The ICDAR 2019 Challenge on "Scanned receipts OCR and key information extraction" (SROIE) covers important aspects related to the automated analysis of scanned receipts, and is considered to evolve into a useful resource for the community, drawing further attention and promoting research and development efforts in this field.

TL;DR: Both text detection and recognition algorithms based on the proposed convolutional neural network based text structure feature extractor achieve state-of-the-art results in two datasets.

TL;DR: In this article, a Chinese positioning, segmenting and identifying method in a natural scene image is presented. But the method does not need supervised training and can be applied to various natural scenes and does not require the use of character stroke characteristics.

TL;DR: Experimental results show that the proposed approach outperforms the existing one with higher recall and much higher recognition accuracy through effective exploitation of joint recognition and correction design.

Abstract: The invention relates to a method and terminal for creating a structured document based on a deep learning model, and belongs to the field of data processing. The method is characterized by presettinga training sample set, wherein each sample in the training sample set comprises a document picture and a labeled document corresponding to the document picture, and the labeled document records position information and category information of each key field in the document picture; training a preset first deep learning model by using the training sample set to obtain a second deep learning model;analyzing the first document picture by the second deep learning model to obtain position information and category information of each key field in the first document picture; and creating a structured document corresponding to the first document picture according to the position information and the category information of each key field in the first document picture, so that the accuracy of converting the document picture into the structured document is improved.