Abstract: Methods, apparatus, and articles manufacture to decode documents based on images using artificial intelligence are disclosed. An example apparatus includes a model executor to input an image into a first artificial intelligence (AI)-based model to generate detected columns of text in the image; and input the image into a second AI-based model to classify the detected columns into categories; a cell identifier to identify rows or cells in the detected columns; and a report generator to: link information corresponding to the rows or cells in the detected columns with corresponding categories; and generating a report based on the linked information.

Abstract: Methods, systems, articles of manufacture and apparatus are disclosed to label text on images. An example apparatus includes colorizer circuitry to apply color to text boxes corresponding to optical character recognition (OCR) data associated with an image, OCR manager circuitry to render an OCR text prompt associated with the OCR data, the OCR text prompt to be rendered proximate to respective ones of the text boxes, the OCR text prompt to display a text portion of the OCR data, and edit circuitry to (a) render an interface in response to selection of the OCR text prompt, the interface populated with the text portion of the OCR data, and (b) in response to an overwrite input to the interface, update the text portion of the OCR data in a memory corresponding to the image.

Abstract: Methods, apparatus, and articles manufacture to decode documents based on images using artificial intelligence are disclosed. An example apparatus includes a model executor to input an image into a first artificial intelligence (AI)-based model to generate detected columns of text in the image; and input the image into a second AI-based model to classify the detected columns into categories; a cell identifier to identify rows or cells in the detected columns; and a report generator to: link information corresponding to the rows or cells in the detected columns with corresponding categories; and generating a report based on the linked information.

Abstract: An apparatus for automatic detection of the face in a given image and localization of the eye region which is a target for recognizing iris is provided. The apparatus includes an image capturing unit collecting an image of a user; and a control unit extracting a characteristic vector from the image of the user, fitting an extracted vector into a Pseudo 2D Hidden Markov Model (HMM), and an operating method thereof for detecting a face and facial features of the user.

Abstract: An apparatus for recognizing iris in an eye is provided. An image collecting unit collects an image of the eye. A control unit detects whether a user wears a contact lens, based on an edge component on the image of the eye.

Abstract: An apparatus for automatic detection of the face in a given image and localization of the eye region which is a target for recognizing iris is provided. The apparatus includes an image capturing unit collecting an image of a user; and a control unit extracting a characteristic vector from the image of the user, fitting an extracted vector into a Pseudo 2D Hidden Markov Model (HMM), and an operating method thereof for detecting a face and facial features of the user.

Abstract: An apparatus for recognizing iris in an eye is provided. An image collecting unit collects an image of the eye. A control unit detects whether a user wears a contact lens, based on an edge component on the image of the eye.