The present techniques relate to, inter alia, cryptographically-verifiable insurance credentials and cryptographically-verifiable property transfer. The novel methods and systems of decentralized identity discussed herein improve user experience (whether individual or organizational) by moving control over identity from the hands of centralized entities, back to where it belongsi.e., to the hands of individual organizations and users. In one aspect, a method includes obtaining a scanned image; processing the scanned image; transmitting a claim request; and receiving and storing an attestation response, and a computing system includes a processor; and a memory having stored thereon computer-executable instructions that, when executed by the one or more processors, cause the computing system to: receive a claim request; cryptographically verify the claim; and transmit an attestation response.

Imaging systems and techniques are described. An imaging system receives image data of an environment according to a first perspective. The imaging system detects an object in the image data. The imaging system generates, based on the image data, reprojected image data of at least a portion of the environment (e.g., representing at least the object) according to a second perspective that is distinct from the first perspective. In some examples, the imaging system generates and outputs an indicator of a status of the object based on the reprojected image data. In some examples, the indicator of the status of the object can indicate a change in the status of the object, such as a change in an illumination characteristic of a light source, a change in content displayed on a display screen, a change in the object's movement, and the like.

The present techniques relate to, inter alia, cryptographically-verifiable insurance credentials and cryptographically-verifiable property transfer. The novel methods and systems of decentralized identity discussed herein improve user experience (whether individual or organizational) by moving control over identity from the hands of centralized entities, back to where it belongsi.e., to the hands of individual organizations and users. In one aspect, a method includes obtaining a scanned image; processing the scanned image; transmitting a claim request; and receiving and storing an attestation response, and a computing system includes a processor; and a memory having stored thereon computer-executable instructions that, when executed by the one or more processors, cause the computing system to: receive a claim request; cryptographically verify the claim; and transmit an attestation response.

The present techniques relate to, inter alia, cryptographically-verifiable insurance credentials and cryptographically-verifiable property transfer. The novel methods and systems of decentralized identity discussed herein improve user experience (whether individual or organizational) by moving control over identity from the hands of centralized entities, back to where it belongsi.e., to the hands of individual organizations and users. In one aspect, a method includes obtaining a scanned image; processing the scanned image; transmitting a claim request; and receiving and storing an attestation response, and a computing system includes a processor; and a memory having stored thereon computer-executable instructions that, when executed by the one or more processors, cause the computing system to: receive a claim request; cryptographically verify the claim; and transmit an attestation response.

A paper sheet processing method that is to be employed by a paper sheet processing device. The paper sheet processing method involves acquiring image information for a paper sheet, transmitting the acquired image information to an external character recognition device, receiving the results of character recognition by the character recognition device from the character recognition device, and using the results of the character recognition by the character recognition device to process the paper sheet.

Techniques are disclosed for automatic scene detection and character extraction. In one example, audiovisual content with video frames, an audio recording, and timing information is received. A score, based on the frame's visual characteristics, is determined for a first frame and subsequent frames. The first frame's score and subsequent frame's scores are compared to determine if the difference between the scores is above a threshold. When the difference in scores is above a threshold, the subsequent frame is classified as a new scene. The audiovisual content is segmented into scenes and textual characters are identified in at least one frame from each scene. The characters are stored and indexed in a searchable database with the timing information for the scene where the characters were identified. The audio recording is transcribed and the transcribed words are stored and indexed in the searchable database with timing information.

A method of processing an image by an electronic device, includes: obtaining a label image of a label including at least one symbol associated with handling of clothing item; obtaining, from the label image, text information associated with the handling of the clothing item; identifying, from the label image, the at least one symbol associated with the handling of the clothing item, based on the text information and the label image; and obtaining handling information related to the clothing item based on the identified at least one symbol.

A system and method for table conversion including converting a table containing text in tabular form to an image, labeling each text area of the image with a bounding box, determining for each bounding box, a position information, a semantic information, and an image information, reconstructing the image into a graph form having a plurality of nodes, wherein each node represents the bounding box of the text areas of the image, inputting at least two nodes into a trained neural network to determine a relative relationship between the at least two nodes, building a knowledge graph using the relative relationship of the at least two nodes, and translating the knowledge graph into machine readable natural language.

Systems and techniques are provided for automatically analyzing and processing domain-specific image artifacts and document images. A process can include obtaining a plurality of document images comprising visual representations of structured text. An OCR-free machine learning model can be trained to automatically extract text data values from different types or classes of document image, based on using a corresponding region of interest (ROI) template corresponding to the structure of the document image type for at least initial rounds of annotations and training. The extracted information included in an inference prediction of the trained OCR-free machine learning model can be reviewed and validated or corrected correspondingly before being written to a database for use by one or more downstream analytical tasks.

An information processing apparatus according to the present disclosure acquires a translation text by executing a translation process on an input text; selects one or more consecutive characters in the translation text as a selection text, based on a user operation; assigns a label selected based on a user operation, to a character string corresponding to the selection text in the input text; and stores the input text to which the label has been assigned, in a storage unit.