Methods and systems are provided for managing identifying information for an entity. The identifying information of the entity embedded in or associated with a digital image is detected, wherein the identifying information is selected from the group consisting of: text information and image information corresponding to one or more features of an entity. The text information may be removed from the digital image. The image information may be replaced with one or more computer generated synthetic images, wherein the computer generated synthetic images are based on a natural appearance of the digital image. The synthetic content, which may be generated by a GAN, is based on a natural appearance of the image. The medical image may also contain PHI in text-based fields associated with private tags/fields, which are automatically identified and removed using the systems and methods provided herein.

An electronic device and a control method therefor are provided. The present electronic device comprises: a communication interface including a circuit, a memory for storing at least one instruction, and a processor for executing the at least one instruction, wherein the processor acquires contents through the communication interface, acquires information about a text included in an image of the contents, and acquires, on the basis of the information about the text included in the image of the contents, caption data of the contents by performing voice recognition for voice data included in the contents.

Embodiments of the present disclosure provide a method, an apparatus, a device, and a medium for generating captioning information of multimedia data. The method includes extracting characteristic information of multimedia data to be processed, wherein the multimedia data comprises a video or an image; and generating a text caption of the multimedia data based on the extracted characteristic information. According to the method provided in the embodiments of the present disclosure, the accuracy of the generated text caption of the multimedia data can be effectively improved.

Workflows for automatic measurement of Doppler is provided. In various embodiments, a plurality of frames of a medical video are read. A mode label indicative of a mode of each of the plurality of frames is determined. At least one of the plurality of frames is provided to a trained feature generator. The at least one of the plurality of frames have the same mode label. At least one feature vector is obtained from the trained feature generator corresponding to the at least one of the plurality of frames. At least one feature vector is provided to a trained classifier. A valve label indicative of a valve is obtained from the trained classifier corresponding to the at least one of the plurality of frames. One or more measurement is extracted indicative of a disease condition from those of the at least one of the plurality of frames matching a predetermined valve label.

Techniques for acoustic management of entertainment devices and systems are described. Various embodiments may include techniques for acoustically determining a location of a remote control or other entertainment device. Some embodiments may include techniques for controlling one or more entertainment components using voice commands or other acoustic information. Other embodiments may include techniques for establishing a voice connection using a remote control device. Other embodiments are described and claimed.

An assembly includes a head mount such as smart glasses wearable on a head of a user. An imager is on the head mount and is configured to generate images of objects. A processor accesses the images responsive to a query and presents images of objects on a display of the head mount to assist the user in identifying, for example, where a lost object was last seen.

A game-agnostic event detector can be used to automatically identify game events. Game-specific configuration data can be used to specify types of pre-processing to be performed on media for a game session, as well as types of detectors to be used to detect events for the game. Event data for detected events can be written to an event log in a form that is both human- and process-readable. The event data can be used for various purposes, such as to generate highlight videos or provide player performance feedback. The event data may be determined based upon output from detectors such as optical character recognition (OCR) engines, and the regions may be upscaled and binarized before OCR processing.

The disclosure provides a display device, and a method for adjusting a position of a video chat window. The method includes: when a video chat window is floating on a playing image for display, acquiring the position of the video chat window and a position of the focus when an instruction for moving a focus is received; determining, according to the position of the video chat window and the position of the focus, whether the video chat window blocks the focus; and in response to the video chat window blocking the focus, moving the video chat window from a current position to a first target position.

Disclosed is a display apparatus. The display apparatus includes a communication interface that receives an image from an external electronic device, a display that displays the image, and a processor, wherein the processor generates a user interface (UI) mask including probability information that a plurality of areas included in the image correspond to a UI, by using a convolutional neural network (CNN) algorithm, identifies a UI area included in the image by using the UI mask, identifies a text area included in the UI area, and recognizes text included in the text area.

A computing system automatically detects, within a digital video frame, a video frame region that depicts a textual expression of a scoreboard. The computing system (a) engages in an edge-detection process to detect edges of at least scoreboard image elements depicted by the digital video frame, with at least some of these edges being of the textual expression and defining alphanumeric shapes; (b) applies pattern-recognition to identify the alphanumeric shapes; (c) establishes a plurality of minimum bounding rectangles each bounding a respective one of the identified alphanumeric shapes; (d) establishes, based on at least two of the minimum bounding rectangles, a composite shape that encompasses the identified alphanumeric shapes that were bounded by the at least two minimum bounding rectangles; and (e) based on the composite shape occupying a particular region, deems the particular region to be the video frame region that depicts the textual expression.