A determination device (10) includes: a reception unit (15a) that receives operation events; an estimation unit (15b) that estimates a determination criterion for determining identity of the operation events on the basis of an attribute value of an operation log included in the operation events; and a determination unit (15c) that determines identity for an operation event to be processed on the basis of the determination criterion.

The present disclosure discloses an electronic counter scale intelligent verification method based on deep learning detection and identification, which includes: collecting a top image, top depth data, and a front image of the electronic counter scale, and selecting a reading display apparatus on the front image; inputting the top image into a scale pan detection and identification model to obtain a scale pan target detection result, verifying the result with the top depth data, obtaining a spatial position of a scale pan, and outputting the spatial coordinates of the four vertices of the scale pan; inputting the top image into an indicating value detection and identification model to obtain indicating value characters and a position of the display apparatus, correcting similar characters and low-confidence characters, and obtaining an indicating value of the electronic counter scale; and performing unmanned verification of weighing performance, repeatability, bias load, and discrimination.

The present disclosure discloses an electronic counter scale intelligent verification method based on deep learning detection and identification, which includes: collecting a top image, top depth data, and a front image of the electronic counter scale, and selecting a reading display apparatus on the front image; inputting the top image into a scale pan detection and identification model to obtain a scale pan target detection result, verifying the result with the top depth data, obtaining a spatial position of a scale pan, and outputting the spatial coordinates of the four vertices of the scale pan; inputting the top image into an indicating value detection and identification model to obtain indicating value characters and a position of the display apparatus, correcting similar characters and low-confidence characters, and obtaining an indicating value of the electronic counter scale; and performing unmanned verification of weighing performance, repeatability, bias load, and discrimination.

A system can include a processor in communication with a data store. The processor can obtain personal identifiable information (PII) data and segregate the PII data into two or more secondary representations. The processor can generate a plurality of co-occurrence matrices based on the two or more secondary representations. The processor can perform a convolution between each of the plurality of co-occurrence matrices and one of a plurality of Gaussian kernels, wherein each of the plurality of Gaussian kernels comprises a different width. The processor can generate a tertiary representation of the PII data by performing a linear combination of the plurality of co-occurrence matrices. The processor can generate a vector based on the tertiary representation and perform a lossy tokenization process on the vector to generate a token. The processor can store the token at the data store.

A system can include a processor in communication with a data store. The processor can obtain personal identifiable information (PII) data and segregate the PII data into two or more secondary representations. The processor can generate a plurality of co-occurrence matrices based on the two or more secondary representations. The processor can perform a convolution between each of the plurality of co-occurrence matrices and one of a plurality of Gaussian kernels, wherein each of the plurality of Gaussian kernels comprises a different width. The processor can generate a tertiary representation of the PII data by performing a linear combination of the plurality of co-occurrence matrices. The processor can generate a vector based on the tertiary representation and perform a lossy tokenization process on the vector to generate a token. The processor can store the token at the data store.

An electronic device is provided. The electronic device includes a display and at least one processor, wherein the at least one processor can be configured to identify a first tilt between a first handwriting input displayed on the display and a first preceding handwriting input that precedes the first handwriting input, the first handwriting input corresponding to a first block, identify a second tilt between a second handwriting input displayed on the display and a second preceding handwriting input that precedes the second handwriting input, the second handwriting input being continuous to the first handwriting input, use the first tilt and the second tilt to determine whether the second handwriting input corresponds to the first block or corresponds to a second block differing from the first block, and perform, based on the second handwriting input corresponding to the second block, at least one operation for processing a plurality of handwriting inputs indicating the second block.

An electronic device is provided. The electronic device includes a display and at least one processor, wherein the at least one processor can be configured to identify a first tilt between a first handwriting input displayed on the display and a first preceding handwriting input that precedes the first handwriting input, the first handwriting input corresponding to a first block, identify a second tilt between a second handwriting input displayed on the display and a second preceding handwriting input that precedes the second handwriting input, the second handwriting input being continuous to the first handwriting input, use the first tilt and the second tilt to determine whether the second handwriting input corresponds to the first block or corresponds to a second block differing from the first block, and perform, based on the second handwriting input corresponding to the second block, at least one operation for processing a plurality of handwriting inputs indicating the second block.

An information obtaining method includes obtaining an image of a design printed on a printing target. The design includes an identifier corresponding to specific information. The information obtaining method further includes identifying the identifier included in the design based on the image; and obtaining the specific information corresponding to the identifier based on the identifier.

An information obtaining method includes obtaining an image of a design printed on a printing target. The design includes an identifier corresponding to specific information. The information obtaining method further includes identifying the identifier included in the design based on the image; and obtaining the specific information corresponding to the identifier based on the identifier.

A method, carried out by one or more processors, for analysing the placement in a user interface, by an electronic device, of digital assets, the method comprising scanning image data of a user interface of an electronic device, capturing image data of an instance of the user interface of the electronic device, identifying a parameter of one or more digital assets in the captured image data.