Methods and systems are described herein for identifying the location and nature of any blur within one or more images received as a user communication and generating an appropriate correction. The system utilizes a first machine learning model, which is trained to identify blurred components of inputted images and determine whether the blurred components are located in portions of the inputted images comprising textual information. The system may apply a corrective action selected by the first machine learning model, which may comprise stitching blurred images together to a sharp product image and/or some other method appropriate for rectifying images received.

An apparatus and method for generating a schema, the apparatus comprising at least a processor and a memory communicatively connected to the at least a processor, the memory containing instructions configuring the at least a processor to display, at a graphical control interface, a content field window, receive, as a function of the content field window, a criterion element, and generate a schema as a function of the criterion element.

An object management system includes an acquisition means for acquiring an image in which a surface of a registration target object, having a circle and a handwritten character drawn thereon, is captured, a generation means for detecting an ellipse corresponding to the circle from the image and generating a registration image in which the image is applied with projective transformation such that the ellipse becomes a circle, and a registration means for writing the registration image into a storage means as data for determining the sameness of the registration target object.

Techniques for performing multi-sensor calibration on a vehicle are described. A method includes obtaining, from each of at least two sensors located on a vehicle, sensor data item of a road comprising a lane marker, extracting, from each sensor data item, a location information of the lane marker, and calculating extrinsic parameters of the at least two sensors based on determining a difference between the location information of the lane marker from each sensor data item and a previously stored location information of the lane marker.

An object is to improve character recognition accuracy of handwritten characters, originally a single continuous character string, described discontinuously. An image area corresponding to a handwritten character is separated from a document image obtained by scanning a document and a character block including characters having the same baseline is extracted. Then, in a case where a plurality of character blocks is extracted from the first image area, a single character block is generated by combining character blocks based on a position relationship of the plurality of character blocks.

Disclosed herein are designs for two baselines to detect products in a retail setting. A novel detector, referred to herein as RetailDet, detects quadrilateral products. To match products using visual texts on 2D space, text features are encoded with spatial positional encoding and the Hungarian Algorithm that calculates optimal assignment plans between varying text sequences is used.

A method for extracting data from a single-layer raster navigational chart (RNC) comprising: using a computer vision algorithm to extract color, text and symbol data from the RNC, storing the color, text, and symbol data in a database, and building an RNC data vector based solely on the color, text, and symbol data of the RNC, wherein the RNC data vector identifies geographical features shown in the RNC and a location of the geographical features' corresponding pixels in the RNC; and drawing a region of interest on the navigational chart based on user input and the RNC data vector, wherein a perimeter of the region of interest is georeferenced with latitude and longitude information.

A method for text-image integration is provided. The method may include receiving a question related to pairable data comprising text data and image data. Embeddings are generated from the text tokens and image encodings. Embeddings are generated from the text tokens and image encodings. The embeddings include text embeddings and image embeddings. A spectral conversion of the text embeddings and the image embeddings is performed to generate spectral data. The spectral data is processed to extract text-image features. The text-image features are processed to generate inferred answers to the question.

An analog meter reading system is applied to an analog meter provided with a scale and a pointer and reads a measured value of the analog meter. The analog meter reading system includes: a unique information acquisition unit that acquires unique information of the analog meter; an image acquisition unit that acquires an image of the analog meter for reading the measured value; a detection unit that detects a reference point on the scale and a pointer from the image; a rotation angle calculation unit that calculates a rotation angle of the pointer until a state in which the pointer points to the reference point changes to a state in which the pointer points to the measuring point based on the reference point and the pointer that are detected; and a measured value conversion unit that converts the rotation angle into the measured value using the unique information.

A data processing method and apparatus, a computer device, a readable storage medium, and a computer program product are provided. The method includes: displaying a shot picture in a shooting interface, the shot picture being captured by a shooting component and including a target object; displaying a first virtual rendering area of the target object in the shooting interface in response to a first trigger operation for the target object in the shooting interface; and displaying media data in the first virtual rendering area, the media data being associated with an object classification of the target object.