Method, apparatus and computer program for providing a personalized study plan to a learner through cognitive and behavioral diagnosis of the learner. A learner who uses a data input device such as a smart pen and a stylus pen by using data obtained from the data input device. The method, apparatus and computer program relate to technology for obtaining input data based on information inputted by a user for at least one question with the data input device, creating test behavior data on the user from the obtained input data, analyzing cognition and behavior of the user based on at least one of metadata on the at least one question and the created test behavior data, and providing a personalized study plan to the user through an algorithm using machine learning based on the cognition and behavior analysis.

A content capturing system is suitable for capturing content in an image of a document. The content capturing system includes a processor and a storage device. The processor accesses the program stored in the storage device to implement a cutting module and a processing module. The cutting module receives a corrected image. The content in the corrected image includes a plurality of text areas, and the cutting module inputs the corrected image or a first text area into a convolutional neural network. The convolutional neural network outputs the coordinates of the first text area. The cutting module cuts the first text area according to the coordinates of the first text area. The cutting module inputs the cut first text area into a text recognition system and obtains a plurality of first characters in the first text area from the text recognition system.

This invention relates to a method of classification of images among different classes comprising: performing a dimensionality reduction step for said different classes on a training set of images whose classes are known, and then classifying one or more unknown images among said different classes with reduced dimensionality, said dimensionality reduction step being performed on said training set of images by machine learning including processing, for at least a first matrix and for at least a second matrix, a parameter representative of a product of two first and second matrices to assess to which given classes several first given images respectively belong: first matrix representing the concatenation, for said several first given images, of the values of the pixels of each said first given image, second matrix representing the concatenation, for said several first given images, of the values of differences between the pixels of each said first given image and the pixels of a second given image different from said first given image but known to belong to same class as said first given image, wherein: a quantum singular value estimation is performed on first matrix, a quantum singular value estimation is performed on second matrix, both quantum singular value estimation of first matrix and quantum singular value estimation of second matrix are combined together, via quantum calculation, so as to get at a quantum singular value estimation of said product of both first and second matrices, said quantum singular value estimation of said product of both first and second matrices being said parameter representative of said product of two first and second matrices processed to assess to which given classes said several first given images respectively belong.

An electronic apparatus and a data transmission method thereof are provided. The data transmission method is adapted to an electronic apparatus including a screen, and the data transmission method includes the following steps. An image frame is displayed through the screen. A selection marquee is displayed on the image frame through the screen, and the selection marquee is configured for selecting a partial image frame from the image frame. Connection information is displayed within the selection marquee through the screen, and feature information of data to be transmitted is recognized from the partial image frame selected by the selection marquee. A connection with another electronic apparatus is established according to the connection information. The data to be transmitted is sent to the another electronic apparatus via the connection according to the feature information.

An image encoder is provided including circuitry and a memory coupled to the circuitry. The circuitry, in operation, responds to a size of a block satisfying a size condition by generating a prediction image using a prediction mode selected from a plurality of prediction modes. The plurality of prediction modes include a first prediction mode in which a prediction process uses a motion vector and a reference block in a same picture as the block. The circuitry encodes the block using the prediction image.

Methods and systems for transforming at least a portion of a physical document into digital data. One method includes obtaining a first plurality of data items automatically extracted from a first physical document and a validated value for a data field. The method also includes automatically identifying a first linked data item included in the first plurality of data items that is linked to the validated value and setting a physical position included in a rule to the physical position of the first linked data item. In addition, the method includes obtaining a second plurality of data items automatically extracted from a second physical document and automatically identifying a candidate data item included in the second plurality of data items based on the rule. Furthermore, the method includes automatically populating a value for the data field for the second physical document based on the candidate data item.

The presently disclosed inventive concepts are directed to systems, computer program products, and methods for intelligent screen automation. The inventive computer program products include program instructions configured to cause a computer, upon execution thereof, to perform a method including: identifying, from among a plurality of elements within one or more images of a user interface, a first set of elements and a second set of elements, wherein the first set of elements and the second set of elements each independently comprise either or both of: textual elements, and non-textual elements; determining one or more logical relationships between the textual elements and the non-textual elements; building a hierarchy comprising some or all of the first set of elements and some or all of the second set of elements, wherein building the hierarchy forms a data structure representing functionality of the user interface; and outputting the data structure to a memory.

An image processing method and apparatus for a smart pen, and an electronic device are provided in embodiments of the present disclosure, and belong to the technical field of data processing. The method comprises: monitoring a working state of a second pressure switch provided at a pen tip of the smart pen when the smart pen is in a working state; controlling an infrared transceiver circuit on the smart pen to send an infrared signal to an area where the smart pen writes; performing feature calculation on an original image by using a first part of a preset lightweight network model; performing feature retrieval on a first feature image to obtain a trajectory identification result corresponding to the original image; and sending, by means of a Bluetooth module on the smart pen, a trajectory vector to a target object with which the smart pen establishes a communication connection.

A method of authenticating an identity document based on an extraction, by analysis of an image acquired of the identity document, of candidate information representative of the appearance of a photograph such as depicted in the acquired image and optically readable data as depicted in the acquired image.

A method includes obtaining sensor data from a plurality of sensors disposed at a plurality of routing control locations of an environment, where the sensor data is indicative of a number of a plurality of pallets at the plurality of routing control locations. The method includes calculating a plurality of difference values based on the sensor data, calculating a transient production value based on the sensor data and a transient objective function, and calculating a steady state production value based on the sensor data and a steady state objective function. The method includes generating a state vector based on the plurality of difference values, the transient production value, and the steady state production value, and defining a set of routes for a set of pallets from among the plurality of pallets based on the state vector and a digital twin of the environment.