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.

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.

Systems and methods for digital identity verification are disclosed. In one embodiment, in an information processing apparatus comprising at least one computer processor, a method for digital identify verification may include: (1) receiving, from a user electronic device or at a website, an image of an identity document for a user, the identity document comprising an image of the user; (2) processing the identity document with at least one business-specific rule; (3) extracting identity information from the identity document; (4) determining a match rate of the image of the user on the identity document to a captured image; (5) assigning a verification score to the user based on extracted identity information and the match rate; and (6) publishing the verification score to at least one system.

A domain alignment technique for cross-domain object detection tasks is introduced. During a preliminary pretraining phase, an object detection model is pretrained to detect objects in images associated with a source domain using a source dataset of images associated with the source domain. After completing the pretraining phase, a domain adaptation phase is performed using the source dataset and a target dataset to adapt the pretrained object detection model to detect objects in images associated with the target domain. The domain adaptation phase may involve the use of various domain alignment modules that, for example, perform multi-scale pixel/path alignment based on input feature maps or perform instance-level alignment based on input region proposals.

A domain alignment technique for cross-domain object detection tasks is introduced. During a preliminary pretraining phase, an object detection model is pretrained to detect objects in images associated with a source domain using a source dataset of images associated with the source domain. After completing the pretraining phase, a domain adaptation phase is performed using the source dataset and a target dataset to adapt the pretrained object detection model to detect objects in images associated with the target domain. The domain adaptation phase may involve the use of various domain alignment modules that, for example, perform multi-scale pixel/path alignment based on input feature maps or perform instance-level alignment based on input region proposals.

The present disclosure provides systems and methods for generating title reports in standardized formats and providing an environment for exchanging the title reports. The system can receive property documents from a plurality of sources. The property documents can be appended with metadata so as to enable the system to order the property documents within a title report. In some examples, generated title reports can accessible within a cloud environment for requesting entities to access.

Methods and systems are presented for providing a machine learning model framework configured to perform complex data classifications. Upon receiving a request for classifying data, the data is recursively assigned to one or more clusters. During each iteration of clustering assignment, a set of clusters is selected based on a previously assigned cluster for the data, and the data is then assigned to a particular cluster from the selected set of clusters. The machine learning model framework also includes a plurality of machine learning models configured to perform simple data classifications. A particular machine learning model is selected from the plurality of machine learning model based on the one or more clusters to which the document is assigned. The particular machine learning model is then used to classify the document.

The present disclosure generally relates to systems that include an artificial intelligence (AI) architecture for determining whether an image is manipulated. The architecture can include a constrained convolutional layer, separable convolutional layers, maximum-pooling layers, a global average-pooling layer, and a fully connected layer. In one specific example, the constrained convolutional layer can detect one or more image-manipulation fingerprints with respect to an image and can generate feature maps corresponding to the image. The global average-pooling layer can generate a vector of feature values by averaging the feature maps. The fully connected layer can then generate, based on the vector of feature values, an indication of whether the image was manipulated or not manipulated.

A tool is needed for music instrument learners to get feedbacks on the correctness of their performances of a particular piece of music. The invention disclosed here is such a tool that can provide music instrument players instant feedback on note pitch and rhythms accuracy based on sheet music. This is accomplished through audio signal processing, sheet music image processing, and conversion of both analogue images and audio signals into standard digital music representation so a comparison can be done and hence a feedback can be presented to the player. An advanced feature will allow users to save the data to the cloud and retrieve later for comparison of progress. It also will allow user to participate an online competition with other players of the same piece of music.

The application provides an information processing device, system and method. The information processing device mainly includes a storage module and a data processing module, where the storage module is configured to receive and store input data, instruction and output data, and the input data includes one or more key features; the data processing module is configured to identify the key features included in the input data and score the input data in the storage module according to a judgment result. The information processing device, system and method provided by the application automatically scores text, pictures, audio, video, and the like instead of manually scoring, which is more accurate and faster.