A communication system includes circuitry. The circuitry receives an input of language information. The circuitry performs recognition on the input language information. The circuitry displays one or more images corresponding to the input language information on a display, based on a result of the recognition.

A method and a system for converting a font of a Chinese character in an image, a computer device and a medium are disclosed. A specific implementation of the method includes: acquiring a stroke of a to-be-converted Chinese character in the image and spatial distribution information of the stroke; and generating a Chinese character in a target font that corresponds to the to-be-converted Chinese character in the image according to the stroke of the to-be-converted Chinese character, the spatial distribution information of the stroke and standard stroke information of the target font, to replace the to-be-converted Chinese character.

A calligraphy-painting device, a calligraphy-painting apparatus, and an auxiliary method for calligraphy-painting are disclosed. The calligraphy-painting device includes: a display portion, configured to display a preset calligraphy-painting information; an image acquiring portion, configured to acquire an image; and a control unit, in communication connection with the display portion, and configured to control the display portion to display the preset calligraphy-painting information, wherein the image is processed to obtain a calligraphy-painting region, and the preset calligraphy-painting information is virtually displayed in the calligraphy-painting region.

A texture recognition device and an operation method of a texture recognition device are provided. The texture recognition device includes a light source array and an image sensor array. The light source array includes a plurality of light sources; the image sensor array is at a side of the light source array and includes a plurality of image sensors, and the plurality of image sensors are configured to receive light emitted from the plurality of light sources and reflected to the image sensors by a texture for a texture image collection; each of the image sensors includes a plurality of signal switches, and a signal of each of the image sensors is read through the plurality of signal switches for forming one image pixel of the texture image.

An electronic device and method are disclosed herein. The electronic device includes: a processor, and a memory operatively connected to the processor. The processor implements the method, including: receive an input of handwritten text including characters, set corpus line key points indicating a substantial-top positions of the characters included in the handwritten text and base line key points indicating a substantial bottom positions of the characters, calculate at least a first feature value based on at least one corpus line key point from among the corpus line key points, and a second feature value based on at least one extracted base line key point from among the base line key points, respectively, input the calculated first feature value into a first neural network to cause the first neural network to generate a first result value, input the calculated second feature value into a second neural network to cause the second neural network to generate a second result value, and input the first result value and the second result value into a fully connected neural network to generate a third result value.

In some embodiments, a method inputs a set of images into a network and trains the network based on a classification of the set of images to one or more characters in a set of characters. The method obtains a set of encodings for the one or more characters based on a layer of the network that restricts the output of the layer to a number of values. Then, the method stores the set of encodings for the one or more characters, wherein an encoding in the set of encodings is retrievable when a corresponding character is determined.

Disclosed herein is a method for facilitating learning of a language through gamification. Accordingly, the method includes receiving, using a communication device, a request for learning the language from a user device. Further, the method includes retrieving, using a storage device, a character of characters based on the request. Further, the method includes transmitting, using the communication device, the character to the user device. Further, the method includes receiving, using the communication device, a user stroke corresponding to a stroke of the character from the user device. Further, the method includes analyzing, using a processing device, the user stroke and the stroke. Further, the method includes determining, using the processing device, a similarity between the user stroke and the stroke. Further, the method includes generating, using the processing device, a reward based on the determining. Further, the method includes transmitting, using the communication device, the reward to the user device.

A method for table extraction from journal literature based on text state characteristics is disclosed. The method includes: constructing a table model according to characteristics of tables in journal literature, where the table model includes two parts: a table caption and table content, building a text line set, table detection, table data positioning, table reconstruction, building a cell data set, restoring data of merged cells, checking the cell data set, and outputting table data. The method is particularly designed based on characteristics of tables such as three-line tables widespread in PDF journal literature, which can realize accurate and correct extraction of specific tables in the PDF journal literature, and especially can ensure a logic relationship of a three-line table. The whole process neither requires manual intervention or interaction nor requires table selection, so that the whole extraction process is automatic.

A system and method for determining a sentiment, a gender and an age group of a subject in a video while the video is being played back. The video is separated into visual data and audio data, the video data is passed to a video processing pipeline and the audio data is passed to both an acoustic processing pipeline and a textual processing pipeline. The system and method performs, in parallel, a video feature extraction process in the video processing pipeline, an acoustic feature extraction process in the acoustic processing pipeline, and a textual feature extraction process in the textual processing pipeline. The system and method combines a resulting visual feature vector, acoustic feature vector, and a textual feature vector into a single feature vector, and determines the sentiment, the gender and the age group of the subject by applying the single feature vector to a machine learning model.

Apparatus and method for detecting hidden encoding of text strings, such as Internet web-domain addresses or email addresses, using optical character recognition (OCR) techniques. In some embodiments, a first set of digital data having a first string of text character codes are converted into an image. Optical character recognition (OCR) is applied to the image to generate a second set of digital data having a second string of text character codes based on detection of the image. The first string of text character codes are compared to the second string of text character codes to detect the presence or absence of hidden codes in the first set of digital data. In some cases, a smoothing function such as Gaussian blurring is applied to degrade the image prior to the application of OCR.