A system for election document processing is disclosed. Image data representative of a scanned election document is matched with a template for processing and consideration of a new elections record. The template defines areas of interest and rules for processing the image data. Data associated with picture elements defining the areas of interest is applied to predetermined validation functions to validate whether the image data includes sufficient information for populating predefined fields and accepting the scanned election document. Additional functions are applied to the image data to compare the image data with information of a voter registration database in order to verify a voter associated with the election document. The scanned election document is further processed for validation sampling.

Provided are a consultation service apparatus of an automatic civic service system and an information processing method. A user holds an application document and identity credentials and operates a consultation service apparatus at a public area. The consultation service apparatus is connected to at least one business/institutional organization at a remote end through a network. The consultation service apparatus acquires image information of the application document and the identity credentials through an image scanner, confirms validity of the image information and performs service classification thereon, transmits the image information to a corresponding organization according to a classification result, and generates a certificate of completion for proof of completion of all procedures. By virtue of the automatic application submission mechanism, social cost can be reduced and working efficiency can be enhanced.

An information processing apparatus includes a processor configured to execute first preprocessing on acquired image data, and execute second preprocessing on a specified partial region of the image data as a target in a case where information for specifying at least one partial region in an image corresponding to the image data is received from post processing on which the image data after the first preprocessing is processed.

An information processing apparatus includes a processor configured to receive a first process result as a result of a character recognition process performed on a first document and a second process result as a result of the character recognition process performed on a second document, calculate a cosine similarity in accordance with first position information on multiple specific characters present in the first document and detected in the first process result and second position information on the multiple specific characters present in the second document and detected in the second process result, and if the calculated cosine similarity is equal to or above a predetermined threshold, determine that the first document is identical in format to the second document.

The disclosure discloses an image moderation method, and relates to a field of deep learning, artificial intelligence, computer vision and natural language processing technologies. The solution includes: obtaining a target image to be moderated; labeling the target image to obtain multiple pieces of label information of the target image; obtaining at least one service vertical category to which the target image is to be launched; recognizing whether the multiple pieces of label information contain label information excluded by the service vertical category; and determining that the target image is a forbidden image in the service vertical category in a case that the multiple pieces of label information contain the label information excluded by the service vertical category.

An information processing apparatus includes a processor configured to acquire an image, receive designation of a type of the image, present another type specified from the image in a case where the type does not satisfy a criterion corresponding to the image, and receive re-designation of a type of the image.

A method for training an image recognition model includes: obtaining a training data set, in which the training data set includes first text images of each vertical category in a non-target scene and second text images of each vertical category in a target scene, and a type of text content involved in the first text images is the same as a type of text content involved in the second text image; training an initial recognition model by using the first text images, to obtain a basic recognition model; and modifying the basic recognition model by using the second text images, to obtain an image recognition model corresponding to the target scene.

Apparatus and methods are described including receiving, via a computer processor, at least one image of a portion of a subject's body. One or more features that are present within the image of the portion of the subject's body, and that were artificially added to the image subsequent to acquisition of the image, are identified. In response thereto, an output is generated on an output device.

A system receives an image including a live facial image of the user and an identity document including a photograph of the user. Moreover, the system calculates a facial match score by comparing facial features in the live facial image to facial features in the photograph. The system recognizes data objects and characters in the identity document using optical character recognition (OCR) and computer vision, and then identifies, based on the recognized data objects and characters, a type of the identity document. Further, the system calculates a document validity score by comparing the recognized characters and data objects to character strings and data objects known to be present in the identified type of the identity document. Additionally, the system determines and outputs the user's identity verification status based on comparing the facial match score to a facial match threshold and comparing the document validity score to a document validity threshold.

According to one embodiment, a reading support system includes a processing device. The processing device includes an extractor and a type determiner. The extractor extracts a plurality of regions from a candidate region. The candidate region is a candidate of a region in which a meter is imaged. The regions respectively include a plurality of characters of the meter. The type determiner determines a type of the meter based on positions of the regions.