Boe Technology Group Co., Ltd.

Ruibin Xue

Yue Li

Bingchuan Shi

Jibo Zhao

Guangwei Huang

Xin Li

Tingting Wang

Shuai Yang

Honghong Jia

Rui Zheng

Zhenxing Hao

Provided are a writing trajectory processing method, a touch control device, a writing system and a storage medium. The writing trajectory processing method includes: obtaining writing data of an original writing trajectory, wherein the writing data comprise a plurality of first trajectory points and a plurality of first contact areas corresponding to the plurality of first trajectory points one to one; smoothing the writing data to obtain smoothed writing data; wherein the smoothed writing data comprise a plurality of second trajectory points and a plurality of second contact areas corresponding to the plurality of second trajectory points one to one; determining a plurality of trajectory line widths corresponding to the plurality of second trajectory points one to one based on the plurality of second contact areas; and, displaying the writing trajectory based on the plurality of second trajectory points and the plurality of trajectory line widths.

Writing trajectory processing method, touch control device, writing system and storage medium

A method and apparatus for recognizing an imaged information-bearing medium, a computer-readable storage device and a computer device are provided. The method comprising: acquiring a first image of the imaged information-bearing medium; performing text recognition on the first image to acquire a text content of the imaged information-bearing medium; classifying the imaged information-bearing medium to acquire a type of the imaged information-bearing medium; and archiving the text content according to the type.

Method and apparatus for recognizing imaged information-bearing medium, computer device and medium

A character recognition method includes: performing feature extraction on an image to be recognized to obtain a first feature map; processing the first feature map to at least obtain N first candidate carrier detection boxes, each first candidate carrier detection box being configured to outline a region of a character carrier; screening the N first candidate carrier detection boxes to obtain K first target carrier detection boxes; performing a feature extraction on the first feature map to obtain a second feature map; processing the second feature map to obtain L first candidate character detection boxes, each first candidate character detection box being configured to outline a region containing at least one character; screening the L first candidate character detection boxes to obtain J first target character detection boxes; and recognizing characters in the J first target character detection boxes to obtain J target character informations.

Character recognition method and terminal device

The present disclosure provides a method for training a convolutional neural network and a method and device for face recognition. By arranging a first training sample set including a first data set and a second data set, the convolutional neural network is trained and may be applied to the face recognition method, an initial face image frame may be extracted from a face detection image, in the face recognition method, a portion above eyes is cropped from the initial face image frame to serve as a target face detection image, thus according to the target face detection image, predicted identity information corresponding to the target face detection image is determined, and then the target face detection image is compared with a face reference image corresponding to the predicted identity information for face recognition.

Method for training convolutional neural network, and method for face recognition and device

The present disclosure provides an answer evaluation method, an answer evaluation system, an electronic device, and a medium. The method comprises: acquiring an answer image, for a test paper answered by a use; classifying the answer image based on a pre-trained test question classification model, so as to obtain an objective question answer area and a subjective question answer area; identifying at least one objective question in the objective question answer area and an objective question answers for each of the at least one objective question; identifying at least one subjective question in the subjective question answer area and a subjective question answers for each of the at least one subjective question; and determining a total score value of the test paper based on the objective question, the objective question answer, the subjective question and the subjective question answer.

Answer evaluation method, answer evaluation system, electronic device, and medium

A handwriting processing method, a touch display device, a computer device, and a storage medium are provided. The handwriting processing method includes: determining, according to a sample point in a writing track that is input by a user by means of a touch display, a group of track points and a related parameter of each track point, the related parameter including a coordinate parameter and a time parameter; determining, according to the related parameter of each track point, a start position, an end position, and a type of a stroke contained in the writing track, where the type of the stroke includes one of a horizontal stroke, a vertical stroke, a left-falling stroke, a right-falling stroke or a lifting stroke; and determining, according to the type of the stroke, a shape of the start position of the stroke.

Handwriting processing method, touch display device, computer device and storage medium

The present disclosure provides a distortion correction method, a distortion correction apparatus, an electronic device, and a computer-readable storage medium, the distortion correction method including: performing a line detection on the distorted image to obtain multiple straight lines in the distorted image; grouping the straight lines into multiple groups of straight lines; selecting optimal boundary lines of the distorted image from the groups of straight lines; determining multiple initial vertexes of the distorted image according to intersection points between the optimal boundary lines; and performing a perspective transformation processing on the distorted image according to the initial vertexes to obtain a corrected image.

Distortion correction method and apparatus, electronic device, and computer-readable storage medium

A voice control method, a voice control device, a computer readable storage medium, and a computer device are disclosed. The voice control method comprises: receiving, in an instruction receiving state, a voice instruction of a user for a specific operation; performing voice processing on the voice instruction to obtain voice information; transmitting, to the user, a request to confirm the voice information; receiving, from the user, a response to the request; and performing the specific operation if the response confirms that the voice information is correct.

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Beijing, China

Ruibin Xue