TY - JOUR A2 - Peña, Antonio J. AU - Zhang, Diandian AU - Liu, Yan AU - Wang, Zhuowei AU - Wang, Depei PY - 2021 DA - 2021/06/01 TI - OCR with the Deep CNN Model for Ligature Script-Based Languages like Manchu SP - 5520338 VL - 2021 AB - Manchu is a low-resource language that is rarely involved in text recognition technology. Because of the combination of typefaces, ordinary text recognition practice requires segmentation before recognition, which affects the recognition accuracy. In this paper, we propose a Manchu text recognition system divided into two parts: text recognition and text retrieval. First, a deep CNN model is used for text recognition, using a sliding window instead of manual segmentation. Second, text retrieval finds similarities within the image and locates the position of the recognized text in the database; this process is described in detail. We conducted comparative experiments on the FAST-NU dataset using different quantities of sample data, as well as comparisons with the latest model. The experiments revealed that the optimal results of the proposed deep CNN model reached 98.84%. SN - 1058-9244 UR - https://doi.org/10.1155/2021/5520338 DO - 10.1155/2021/5520338 JF - Scientific Programming PB - Hindawi KW - ER -