-
公开(公告)号:US11282516B2
公开(公告)日:2022-03-22
申请号:US16278679
申请日:2019-02-18
Inventor: Shuangshuang Qiao , Kun Liu , Yang Liang , Xiangyue Lin , Chao Han , Mingfa Zhu , Jiangliang Guo , Xu Li , Jun Liu , Shuo Li , Shiming Yin
Abstract: Embodiments of the present disclosure provide a human-machine interaction processing method, an apparatus thereof, a user terminal, a processing server and a system. On the user terminal side, the method includes: receiving an interaction request voice inputted from a user, and collecting video data of the user when inputting the interaction request voice; obtaining an interaction response voice corresponding to the interaction request voice, where the interaction response voice is obtained according to expression information of the user when inputting the interaction request voice and included in the video data; and outputting the interaction response voice to the user. The method imbues the interaction response voice with an emotional tone that matches the current emotion of the user, so that the human-machine interaction process is no longer monotonous, greatly enhancing the user experience.
-
公开(公告)号:US20210390294A1
公开(公告)日:2021-12-16
申请号:US17139403
申请日:2020-12-31
Inventor: Xiangkai Huang , Qiaoyi LI , Yulin LI , Ju Huang , Duohao Qin , Xiameng Qin , Minghao Liu , Junyu Han , Jiangliang Guo
Abstract: Embodiments of the present disclosure disclose an image table extraction method and apparatus, an electronic device, a storage media, and a training method for a table extraction model, which relate to the field of artificial intelligence technologies and cloud computing technologies, including: acquiring an image to be processed;
generating a table of the image to be processed according to a table extraction model, where the table extraction model is obtained according to a field position feature, an image feature, and a text feature of a sample image; and filling text information of the image to be processed into the table.-
公开(公告)号:US11138903B2
公开(公告)日:2021-10-05
申请号:US16278690
申请日:2019-02-18
Inventor: Xiangyue Lin , Kun Liu , Shuangshuang Qiao , Yang Liang , Chao Han , Mingfa Zhu , Jiangliang Guo , Xu Li , Jun Liu , Shuo Li , Shiming Yin
Abstract: The present disclosure provides a method, an apparatus, a device and a system for sign language translation, where a server receives video information sent by a terminal device, and preprocesses the video information to obtain at least one sign language action; the at least one sign language action is input into a sign language model for classification and prediction to obtain a word corresponding to the at least one sign language action; each word is input into a language model to determine whether an intention expression is complete; and each word is sent to the terminal device when the intention expression is complete, so that the terminal device displays each word, thereby realizing the translation of the sign language action into text, enabling the ordinary persons to better understand intentions of the hearing impaired, thus improving efficiency of communications.
-
公开(公告)号:US11681875B2
公开(公告)日:2023-06-20
申请号:US16984231
申请日:2020-08-04
Inventor: Xiangkai Huang , Leyi Wang , Lei Nie , Siyu An , Minghao Liu , Jiangliang Guo
IPC: G06F17/00 , G06F40/30 , G06V30/262 , G06V30/413 , G06V30/19 , G06V10/82 , G06V30/412 , G06V30/28
CPC classification number: G06F40/30 , G06V10/82 , G06V30/19173 , G06V30/274 , G06V30/412 , G06V30/413 , G06V30/293
Abstract: The present application discloses a method for image text recognition, an apparatus, a device, and a storage medium, and relates to image processing technologies in the field of cloud computing. A specific implementation is: acquiring an image to be processed, where at least one text line exists in the image to be processed; processing each text line in the image to be processed to obtain a composite encoded vector corresponding to each word in each text line, where the composite encoded vector carries semantic information and position information; and determining a text recognition result of the image to be processed according to the semantic information and the position information carried in the composite encoded vector corresponding to each word in each text line. This technical solution can accurately distinguish adjacent fields with small pixel spacing in the image and improve the accuracy of text recognition in the image.
-
5.
公开(公告)号:US11488294B2
公开(公告)日:2022-11-01
申请号:US16939277
申请日:2020-07-27
Inventor: Yawei Wen , Jiabing Leng , Minghao Liu , Yulin Xu , Jiangliang Guo , Xu Li
Abstract: Provided are a method for detecting display screen quality, an apparatus, an electronic device and a storage medium. The method includes: receiving a quality detection request sent by a console deployed on a display screen production line, the quality detection request including a display screen image collected by an image collecting device on the display screen production line; inputting the display screen image into a defect detection model to obtain a defect detection result, the defect detection model being obtained by training historical defective display screen images using a structure of deep convolutional neural networks and an object detection algorithm; and determining, according to the defect detection result, a defect on a display screen corresponding to the display screen image, a defect category corresponding to the defect, and a position corresponding to the defect.
-
公开(公告)号:US11380232B2
公开(公告)日:2022-07-05
申请号:US16936806
申请日:2020-07-23
Inventor: Yawei Wen , Jiabing Leng , Minghao Liu , Yulin Xu , Jiangliang Guo , Xu Li
IPC: G09G3/00 , G01N21/956
Abstract: A display screen quality detection method, an apparatus, an electronic device and a storage medium. The method includes receiving a quality detection request sent by a console deployed on a display screen production line, where the quality detection request includes a display screen image captured by an image capturing device on the display screen production line, performing image preprocessing on the display screen image, and inputting the preprocessed display screen image into a defect detection model to obtain a defect detection result, where the defect detection model is obtained by training with a historical defect display screen image using a deep convolutional neural network structure and an instance segmentation algorithm, determining, according to the defect detection result, quality of a display screen corresponding to the display screen image. The technical solution has high defect detection accuracy, good system performance, and high business expansion capability.
-
-
-
-
-