Techniques for processing images of documents captured using a mobile device are provided. The images can include different sides of a document from a mobile device for an authenticated transaction. In an example implementation, a method includes inspecting the images to detect a feature associated with a first side of the document. In response to determining an image is the first side of the document, a type of content is selected to be analyze on the image of the first side and one or more of regions of interests (ROIs) are identified on the image of the first side that are known to include the selected type of content. A process can include receiving a sub-image of the image of the first side from the preprocessing unit, and performing content detection test on the sub-image.

The present disclosure relates to a medical image analysis method using a processor and a memory which are hardware. The method includes generating predicted second metadata for a medical image by using a prediction model, and determining a processing method of the medical image based on one of first metadata stored corresponding to the medical image and the second metadata.

The present disclosure relates to a medical image analysis method using a processor and a memory which are hardware. The method includes generating predicted second metadata for a medical image by using a prediction model, and determining a processing method of the medical image based on one of first metadata stored corresponding to the medical image and the second metadata.

Systems and methods are provided for processing and extracting content from an image captured using a mobile device. In one embodiment, an image is captured by a mobile device and corrected to improve the quality of the image. The corrected image is then further processed by adjusting the image, identifying the format and layout of the DL, binarizing the image and extracting the content using optical character recognition (OCR). Multiple methods of image adjusting may be implemented to accurately assess features of the DL, and a secondary layout identification process may be performed to ensure that the content being extracted is properly classified.

A portable writing apparatus includes a writing instrument carriage to hold a writing instrument and an actuator system coupled to the writing instrument carriage to move the writing instrument carriage. A controller is electrically coupled to the actuator system, and the controller includes logic that when executed by the controller causes the controller to perform operations including: receiving input data including a user's handwritten characters; and controlling the actuator system to move the writing instrument carriage in response to the input data. The writing instrument carriage traces a shape of the user's handwritten characters.

Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for detecting text instances of arbitrary shapes, sizes, and locations. In one aspect, a method comprises processing an image depicting one or more text instances, generating a respective prediction for each character in a sequence of characters that are predicted to be depicted in the text instance, the respective prediction comprising a respective character class to which the predicted character belongs, the respective character class selected from a set that includes printable character classes and a space character class and a bounding box that contains the character within the image, and grouping the sequence of characters into a plurality of words based on locations of characters that are predicted to belong to the space character class.

Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for detecting text instances of arbitrary shapes, sizes, and locations. In one aspect, a method comprises processing an image depicting one or more text instances, generating a respective prediction for each character in a sequence of characters that are predicted to be depicted in the text instance, the respective prediction comprising a respective character class to which the predicted character belongs, the respective character class selected from a set that includes printable character classes and a space character class and a bounding box that contains the character within the image, and grouping the sequence of characters into a plurality of words based on locations of characters that are predicted to belong to the space character class.

The present disclosure relates to a medical image analysis method using a processor and a memory which are hardware. The method includes generating predicted second metadata for a medical image by using a prediction model, and determining a processing method of the medical image based on one of first metadata stored corresponding to the medical image and the second metadata.

The present disclosure relates to a medical image analysis method using a processor and a memory which are hardware. The method includes generating predicted second metadata for a medical image by using a prediction model, and determining a processing method of the medical image based on one of first metadata stored corresponding to the medical image and the second metadata.

Systems and methods are provided for processing and extracting content from an image captured using a mobile device. In one embodiment, an image is captured by a mobile device and corrected to improve the quality of the image. The corrected image is then further processed by adjusting the image, identifying the format and layout of the DL, binarizing the image and extracting the content using optical character recognition (OCR). Multiple methods of image adjusting may be implemented to accurately assess features of the DL, and a secondary layout identification process may be performed to ensure that the content being extracted is properly classified.