公开(公告)号：US11756170B2

公开(公告)日：2023-09-12

申请号：US17151783

申请日：2021-01-19

Applicant: BEIJING BAIDU NETCOM SCIENCE TECHNOLOGY CO., LTD.

Inventor： Qunyi Xie ,  Xiameng Qin ,  Yulin Li ,  Junyu Han ,  Shengxian Zhu

IPC: G06T5/00 ,  G06N3/08 ,  G06T5/30

CPC classification number: G06T5/006 ,  G06N3/08 ,  G06T5/30 ,  G06T2207/20081 ,  G06T2207/20084 ,  G06T2207/30176

Abstract: Embodiments of the present disclosure provide a method and apparatus for correcting a distorted document image, where the method for correcting a distorted document image includes: obtaining a distorted document image; and inputting the distorted document image into a correction model, and obtaining a corrected image corresponding to the distorted document image; where the correction model is a model obtained by training with a set of image samples as inputs and a corrected image corresponding to each image sample in the set of image samples as an output, and the image samples are distorted. By inputting the distorted document image to be corrected into the correction model, the corrected image corresponding to the distorted document image can be obtained through the correction model, which realizes document image correction end-to-end, improves accuracy of the document image correction, and extends application scenarios of the document image correction.

公开(公告)号：US20220092353A1

公开(公告)日：2022-03-24

申请号：US17540207

申请日：2021-12-01

Applicant: BEIJING BAIDU NETCOM SCIENCE TECHNOLOGY CO., LTD.

Inventor： Ruixue Liu ,  Xiameng Qin ,  Mengyi En ,  Kun Yao ,  Chengquan Zhang ,  Shengxian Zhu ,  Yunhao Li ,  Junyu Han ,  Hao Sun

IPC: G06K9/62 ,  G06V30/30 ,  G06V30/14

Abstract: A computer-implemented method includes: acquiring training data, the training data includes training images for a preset vertical type, and the training images include a first training image containing real data of the preset vertical type and a second training image containing virtual data of the preset vertical type ; building a basic model, the basic model includes a deep learning network, and the deep learning network is configured to recognize the training images to extract text data in the training image; and training the basic model by using the training data to obtain the image recognition model.