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 for using a mobile device to submit an application for an insurance policy using images of documents captured by the mobile device are provided herein. The information is then used by an insurance company to generate a quote which is then displayed to the user on the mobile device. A user captures images of one or more documents containing information needed to complete an insurance application, after which the information on the documents is extracted and sent to the insurance company where a quote for the insurance policy can be developed. The quote can then be transmitted back to the user. Applications on the mobile device are configured to capture images of the documents needed for an insurance application, such as a driver's license, insurance information card or a vehicle identification number (VIN). The images are then processed to extract the information needed for the insurance application.

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.

An improved machine learning system is provided. For example, a content management server may provide a digital assessment of a user's handwriting to assess the user's knowledge of a language. The assessment may comprise adaptive technology to help determine initial questions to provide to the user as well as follow-up questions to clarify appropriate remediation content in a particular context. The content management server may also provide real-time analysis, including assessing multiple users at the same time in adjusting the assessment based on the digital input from each of these users. In some examples, the content management server may incorporate handwriting analysis methods to perform object detection and score handwriting input.

An improved machine learning system is provided. For example, a content management server may provide real-time analysis of a user's handwriting to assess the user's knowledge of a language, including using a convolution neural network method.

An improved machine learning system is provided. For example, a content management server may provide real-time analysis of a user's handwriting to assess the user's knowledge of a language, including using a convolution neural network method.

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 document, 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 document, and a secondary layout identification process may be performed to ensure that the content being extracted is properly classified.

A text recognition method includes scaling a to-be-recognized image based on a first scale ratio, determining first coordinate information corresponding to a text line area in the scaled to-be-recognized image, determining, based on the first scale ratio, second coordinate information corresponding to the first coordinate information, where the second coordinate information is coordinate information of the text line area in the to-be-recognized image, performing character recognition on text line images corresponding to the second coordinate information by using a recognition model, and determining text line content corresponding to the text line images, where the to-be-recognized image includes the text line images.

A text recognition method includes scaling a to-be-recognized image based on a first scale ratio, determining first coordinate information corresponding to a text line area in the scaled to-be-recognized image, determining, based on the first scale ratio, second coordinate information corresponding to the first coordinate information, where the second coordinate information is coordinate information of the text line area in the to-be-recognized image, performing character recognition on text line images corresponding to the second coordinate information by using a recognition model, and determining text line content corresponding to the text line images, where the to-be-recognized image includes the text line images.

The subject matter of this specification can be implemented in, among other things, a method that includes identifying edges of a section of a document in a source image that includes at least one row of text. The method includes identifying characters in the document. The method includes identifying word portions. The method includes generating polynomials that approximate points of the characters within the word portions. The method includes generating a second polynomial that approximates the points of the characters of word portions. The method includes identifying a stretching coefficient of the row of text based on a length of the section between the edges relative to a length of the second polynomial. The method includes mapping portions of the source image along the row of text to new positions in a corrected image based on the second polynomial and the stretching coefficient.