Abstract: Embodiments disclosed herein provide for dynamically modifying image and/or video content based on user preferences. Embodiments provide a server, a database containing user preference information and one or more content templates, and a content generator comprising a plurality of generative adversarial networks, wherein each generative adversarial network is associated with a corresponding style transfer, and the content generator is configured to apply one or more style transfers to a base image to convert the base image into a desired style. Once created, the customized content is sent to a client device to for display.

Abstract: Techniques are disclosed for improving user experience of multimedia streaming over computer networks. More specifically, techniques presented herein reduce (or eliminate) latency in playback start time for streaming digital media content resulting from digital rights management (DRM) authorizations. A streaming media client (e.g., a browser, set-top box, mobile telephone or tablet “app”) may request a “fast-expiring” license for titles the streaming media client predicts a user is likely to begin streaming. A fast-expiring license is a DRM license (and associated decryption key) which is valid for only a very limited time after being used for playback. During the validity period of such a license, the client device requests a “normal” or “regular” license to continue accessing the title after the fast-expiring license expires.

Abstract: A device receives information indicating first names and last names of individuals and applies different cursive fonts to each of the first names and the last names to generate images of different cursive first names and different cursive last names. The device applies different transformations to the images of the different cursive first names and the different cursive last names to generate a set of first name images and a set of last name images. The device combines each first name image with each last name image to form a set of signature images and trains a neural network model, with the set of signature images, to generate a trained neural network model. The device receives an image of a signature and processes the image of the signature, with the trained neural network model, to recognize a first name and a last name in the signature.

Abstract: Methods and systems for providing changes to a live voice stream of a person are disclosed. A change to be made to the live voice stream based on user information can be identified. The live voice stream can be changed based on the user information.

Abstract: One embodiment of the invention sets forth a mechanism for encoding video streams associated with the same digital content such that switch points staggered across two video streams occur at every offset temporal distance. The offset temporal distance is less than the distance between two consecutive key frames in a given video stream. This enables a content player to switch to a video stream having a playback quality up or down one level from a current video stream at the offset temporal distance from the most recently played key frame. In effect, the content player does not wait the entire key frame temporal distance before switching.

Abstract: Disclosed herein are system, method, and device embodiments for ATM access during a power outage. In an example embodiment, an automated teller machine (ATM) may receive power from a mobile device including a banking application, send the power to a rechargeable battery of the ATM, and enter a reduced power mode, wherein the ATM is powered by the rechargeable battery. Further, the ATM may receive a transaction request including an authentication credential from the banking application, determine an account associated with the authentication credential, determine an authorization result indicating whether to perform the transaction request, and generate recordation information corresponding to the authorization result.

Abstract: Systems and methods are presented for establishing secure transactions among a group of transacting parties through use of multi-party computation including garbled circuits. The system uses a set of distributed garbled circuit servers, each having a garbled circuit module, to collectively and securely perform a transactional function, such that any party only has access to its own input and output. Each garbled circuit module may receive input financial data for a transacting party and financial data for at least one other transacting party, and perform an operation to obtain output financial data. The operation may relate to a function for determining a plurality of financial transactions among the plurality of transacting parties.

Abstract: Systems and methods mediate permissions for applications on user devices using predictive models. Data communications are monitored on a user device for permission requests and responses. A predictive model is trained with these permission requests and responses until a threshold is met. Then, a default permission response is provided on behalf of the user device in response to a permission request.

Abstract: A device receives information indicating first names and last names of individuals and applies different cursive fonts to each of the first names and the last names to generate images of different cursive first names and different cursive last names. The device applies different transformations to the images of the different cursive first names and the different cursive last names to generate a set of first name images and a set of last name images. The device combines each first name image with each last name image to form a set of signature images and trains a neural network model, with the set of signature images, to generate a trained neural network model. The device receives an image of a signature and processes the image of the signature, with the trained neural network model, to recognize a first name and a last name in the signature.

Abstract: Methods and systems disclosed herein describe using machine learning to lock and unlock a device. Machine learning may be trained to recognize one or more features. Once the device has been trained to recognize one or more features, a user may define an unlock condition for the device using the one or more trained features. After defining the unlock condition, the device may be locked by verifying the one or more features that the user defined as the unlock condition using machine learning. When verification is successful, the device may be unlocked and the user allowed to access the device.

Abstract: Systems and methods for connecting datasets are disclosed. For example, a system may include a memory unit storing instructions and a processor configured to execute the instructions to perform operations. The operations may include receiving a plurality of datasets and a request to identify a cluster of connected datasets among the received plurality of datasets. The operations may include selecting a dataset. In some embodiments, the operations include identifying a data schema of the selected dataset and determining a statistical metric of the selected dataset. The operations may include identifying foreign key scores. The operations may include generating a plurality of edges between the datasets based on the foreign key scores, the data schema, and the statistical metric. The operations may include segmenting and returning datasets based on the plurality of edges.

Abstract: An exemplary system, method, and computer-accessible medium can include, for example, receiving an original dataset(s), receiving a synthetic dataset(s), training a model(s) using the original dataset(s) and the synthetic dataset(s), and evaluating the synthetic dataset(s) based on the training of the model(s). The model(s) can include a first model and a second model, and the first model can be trained using the original dataset(s) and the second model can be trained using the synthetic dataset(s). The synthetic dataset(s) can be evaluated by comparing first results from the training of the first model to second results from the training of the second model.

Abstract: The disclosed systems and methods may receive a first salted password having a first password, a first user device identifier, and a first browser identifier, extract the first password, the first user device identifier, and the first browser identifier from the first salted password, and determine whether the first password, the first user device identifier, and the first browser identifier respectively match a stored first password, a stored first user device identifier, and a stored first browser identifier. The systems may grant the request to access the one or more resources for the first user device or perform other actions depending on whether the first password, the first user device identifier, and the first browser identifier respectively match the stored first password, the stored first user device identifier, and the stored first browser identifier.

Abstract: Computer systems and methods for verifying a route taken by a communication are disclosed. In one implementation, a device for verifying a route taken by a communication may include one or more processors configured to obtain a communication transmitted by a source entity. The communication may include data and digital signatures, and each of the digital signatures may be generated based on at least the data. Further, the digital signatures may include a digital signature associated with the source entity, and a set of digital signatures associated with at least a subset of intermediate entities on a route taken by the communication. The one or more processors may be further configured to verify the digital signatures included in the communication, verify whether the entities associated with the digital signatures form an expected route for the communication, and process the data.

Abstract: One embodiment of the invention sets forth a mechanism for encoding video streams associated with the same digital content such that switch points staggered across two video streams occur at every offset temporal distance. The offset temporal distance is less than the distance between two consecutive key frames in a given video stream. This enables a content player to switch to a video stream having a playback quality up or down one level from a current video stream at the offset temporal distance from the most recently played key frame. In effect, the content player does not wait the entire key frame temporal distance before switching.

Abstract: A method includes storing, by one or more processors of one or more computing devices, a plurality of datasets in a non-transitory computer memory associated with the one or more computing devices. A plurality of index representations is generated where each one of the plurality of index representations includes a compressed representation of a respective one of the plurality of datasets. The plurality of index representations is stored in the non-transitory computer memory. A sample dataset is received by the one or more processors. A sample dataset representation is generated that includes a compressed representation of the sample dataset. A determination that at least one of the plurality of datasets is most similar to the sample dataset based on the sample dataset representation and the plurality of index representations is performed.

Abstract: A computer-implemented method includes tracking, by a computing device, user browsing activity of a first page having known elements; mapping, by the computing device, the user browsing activity to the known elements; storing, by the computing device, mapping information that maps the user browsing activity to the known elements; tracking, by the computing device, user browsing activity of a second page having unknown elements; identifying, by the computing device, the unknown elements based on the mapping information and the user browsing activity of the second page; and executing, by the computing device, one or more computer-based instructions based on the determining the unknown elements that were identified.

Abstract: System and devices for live captioning events is disclosed. The system may receive event calendar data and a first plurality of caption files and preselect a first caption file based on the event calendar data. The system may then access an audiovisual recorder of a user device, and receive a first feedback from the recorder. The system may then determine whether the first caption file matches the first feedback. When there is a match, the system may determine a first synchronization between the caption file and the feedback. When there is no match, the system may determine if there is a match with a second caption file of the first plurality of caption files and determine a second synchronization. When the second caption file does not match, the system may receive at least a third caption file over a mobile network and determine a third synchronization for display.