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公开(公告)号：US20230020022A1
公开(公告)日：2023-01-19
申请号：US17885882
申请日：2022-08-11
Inventor： Shanshan LIU , Meina QIAO , Liang WU , Chengquan ZHANG , Kun YAO
Abstract: A method of recognizing a text, which relates to a field of an artificial intelligence technology, in particular to a field of computer vision and deep learning technology, and may be applied to optical character recognition or other applications. The method includes: acquiring a plurality of image sequences by continuously scanning a document; performing an image stitching, so as to obtain a plurality of successive frames of stitched images corresponding to the plurality of image sequences respectively, an overlapping region exists between each two successive frames of stitched images; performing a text recognition based on the plurality of successive frames of stitched images, so as to obtain a plurality of corresponding recognition results; and performing a de-duplication on the plurality of recognition results based on the overlapping region between each two successive frames of stitched images, so as to obtain a text recognition result for the document.
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公开(公告)号：US20220392243A1
公开(公告)日：2022-12-08
申请号：US17890629
申请日：2022-08-18
Inventor： Shanshan LIU , Meina QIAO , Liang WU , Pengyuan LYU , Sen FAN , Chengquan ZHANG , Kun YAO
Abstract: A method for training a text classification model and an electronic device are provided. The method may include: acquiring a set of to-be-trained images, the set of to-be-trained images including at least one sample image; determining predicted position information and predicted attribute information of each text line in each sample image based on each sample image; and training to obtain the text classification model, based on the annotation position information and the annotation attribute information of each text line in each sample image, and the predicted position information and the predicted attribute information of each text line in each sample image, and the text classification model is used to detect attribute information of each text line in an to-be-recognized image.
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公开(公告)号：US20240304015A1
公开(公告)日：2024-09-12
申请号：US18041265
申请日：2022-04-21
Inventor： Sen FAN , Xiaoyan WANG , Pengyuan LV , Chengquan ZHANG , Kun YAO
IPC: G06V30/19 , G06V30/148 , G06V30/18
CPC classification number: G06V30/19167 , G06V30/153 , G06V30/18 , G06V30/19147 , G06V30/1916
Abstract: The present disclosure provides a method of training a deep learning model for text detection and a text detection method, which relates to the technical field of artificial intelligence, and in particular, to the technical field of computer vision and deep learning and can be used in scenarios of OCR optical character recognition. A method of training a deep learning model for text detection is provided, in which a single character segmentation sub-network outputs a single character segmentation prediction result, a text line segmentation sub-network outputs a text line segmentation prediction result, the trained deep learning model can be used for detecting a text area; and, can at the same time achieve single character segmentation and text line segmentation, and thus is capable to perform text detection by combining two ways of text segmentation, which further improves the accuracy of text area detection.
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4.发明公开公开(公告)号：US20230196805A1
公开(公告)日：2023-06-22
申请号：US18168089
申请日：2023-02-13
Inventor： Ju HUANG , Xiaoqiang ZHANG , Xiameng QIN , Chengquan ZHANG , Kun YAO
Abstract: The present disclosure provides a character detection method and apparatus, a model training method and apparatus, a device and a storage medium. The specific implementation is: acquiring a training sample, where the training sample includes a sample image and a marked image, and the marked image is an image obtained by marking a text instance in the sample image; inputting the sample image into a character detection model, to obtain segmented images and image types of the segmented images output by the character detection model, where the image type indicates that the segmented image includes a text instance, or the segmented image does not include a text instance; and adjusting a parameter of the character detection model according to the segmented images, the image types of the segmented images and the marked image.
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公开(公告)号：US20230045715A1
公开(公告)日：2023-02-09
申请号：US17966112
申请日：2022-10-14
Inventor： Chengquan ZHANG , Pengyuan LV , Sen FAN , Kun YAO , Junyu HAN , Jingtuo LIU
Abstract: The present disclosure provides a text detection method, a text recognition method and an apparatus, which relate to the field of artificial intelligence technology, in particular to the field of deep learning and computer vision technologies, and can be applied to scenarios such as optical character recognition. The text detection method is: acquiring an image feature of a text strip in a to-be-recognized image; performing visual enhancement processing on the to-be-recognized image to obtain an enhanced feature map of the to-be-recognized image; comparing the image feature of the text strip with the enhanced feature map for similarity to obtain a target bounding box of the text strip on the enhanced feature map.
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Patent Agency Ranking
公开(公告)号：US20220027611A1
公开(公告)日：2022-01-27
申请号：US17498226
申请日：2021-10-11
Inventor： Yuechen YU , Chengquan ZHANG , Yulin LI , Xiaoqiang ZHANG , Ju HUANG , Xiameng QIN , Kun YAO , Jingtuo LIU , Junyu HAN , Errui DING
Abstract: Provided are an image classification method and apparatus, an electronic device and a storage medium, relating to the field of artificial intelligence and, in particular, to computer vision and deep learning. The method includes inputting a to-be-classified document image into a pretrained neural network and obtaining a feature submap of each text box of the to-be-classified document image by use of the neural network; inputting the feature submap of each text box, a semantic feature corresponding to preobtained text information of each text box and a position feature corresponding to preobtained position information of each text box into a pretrained multimodal feature fusion model and fusing, by use of the multimodal feature fusion model, the three into a multimodal feature corresponding to each text box; and classifying the to-be-classified document image based on the multimodal feature corresponding to each text box.
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公开(公告)号：US20240281609A1
公开(公告)日：2024-08-22
申请号：US18041207
申请日：2022-05-16
Inventor： Pengyuan LV , Jingquan LI , Chengquan ZHANG , Kun YAO , Jingtuo LIU , Junyu HAN
Abstract: The present application provides a method of training a text recognition model. The method includes: inputting a first sample image into the visual feature extraction sub-model to obtain a first visual feature and a first predicted text, the first sample image contains a text and a tag indicating a first actual text; obtaining, by using the semantic feature extraction sub-model, a first semantic feature based on the first predicted text; obtaining, by using the sequence sub-model, a second predicted text based on the first visual feature and the first semantic feature; and training the text recognition model based on the first predicted text, the second predicted text and the first actual text. The present disclosure further provides a method of recognizing a text, an electronic device, and a storage medium.
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公开(公告)号：US20230401828A1
公开(公告)日：2023-12-14
申请号：US17905965
申请日：2022-04-08
Inventor： Meina QIAO , Shanshan LIU , Xiameng QIN , Chengquan ZHANG , Kun YAO
IPC: G06V10/774 , G06V30/14 , G06V10/764
CPC classification number: G06V10/774 , G06V10/764 , G06V30/1444
Abstract: A method for training an image recognition model includes: obtaining a training data set, in which the training data set includes first text images of each vertical category in a non-target scene and second text images of each vertical category in a target scene, and a type of text content involved in the first text images is the same as a type of text content involved in the second text image; training an initial recognition model by using the first text images, to obtain a basic recognition model; and modifying the basic recognition model by using the second text images, to obtain an image recognition model corresponding to the target scene.
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公开(公告)号：US20220101642A1
公开(公告)日：2022-03-31
申请号：US17545765
申请日：2021-12-08
Inventor： Qunyi XIE , Yangliu XU , Xiameng QIN , Chengquan ZHANG
Abstract: The disclosure discloses a method for character recognition, an electronic device, and a storage medium. The technical solution includes: obtaining a test sample image and a test sample character both corresponding to a test task; performing fine-tuning on a trained meta-learning model based on the test sample image and the test sample character to obtain a test task model; obtaining a test image corresponding to the test task; and generating a test character corresponding to the test image by inputting the test image into the test task model.
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公开(公告)号：US20230186664A1
公开(公告)日：2023-06-15
申请号：US18169032
申请日：2023-02-14
Inventor： Shanshan LIU , Meina QIAO , Liang WU , Pengyuan LV , Sen FAN , Chengquan ZHANG , Kun YAO
CPC classification number: G06V30/19173 , G06V30/19147 , G06V30/30
Abstract: A method for text recognition is disclosed. The method includes obtaining a whole-image scenario for an image to be processed and a text image in the image to be processed. The method further includes determining a first text recognition model corresponding to the whole-image scenario. The method further includes performing text recognition on the text image according to the first text recognition model to obtain text information.
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