2123results about "Details involving graphical user interface" patented technology

A soundbar for medical monitoring which may comprise a speaker, a sensor, and a hardware processor. The speaker can be configured to emit audio signals. The sensor can be configured to obtain sensor data relating to a physiology of a subject. The sensor can include a camera and the sensor data can include image data. The hardware processor can be configured to access the sensor data and determine a health status of the subject based on at least the sensor data.

Example implementations are directed to recapturing or realigning a room or scene in an artificial reality (XR) environment as a three dimensional (3D) space. To initially capture a room, a user manually annotates, using an XR system, one or more walls around the XR system. The XR system then aligns or localizes itself relative to the room. Once a room is captured and stored, and the user in the future enters the room again, the XR system may not be able to align itself in the room due to, for example, lighting conditions. Rather than require the user to manually recapture every wall captured during the initial room capture, the XR system can select one wall for recapture and, after receiving an annotation or marking of the one wall from the user, use the selection to realign the XR system relative to the room.

A symbolic neuroadaptive control system is disclosed for real-time arbitration, consent, and ethical modulation of artificial intelligence agents operating in wearable computing environments. The system integrates multimodal biometric telemetry—including high-resolution EEG signals—with a symbolic kernel that performs logic-driven arbitration over cognitive, emotional, and ethical states. Using Coq-verified invariants and zero-knowledge biometric consent tokens, the system constructs a deterministic symbolic execution graph, gating AI outputs based on internal user states such as trauma, stress, or intentionality. Unlike conventional black-box BCI models, the invention routes EEG-inferred affective-symbolic tokens through a formal ethics layer that enforces real-time interrupt control, utility bounding, and trust verification. The kernel enables AGI systems to defer or modify behavior based on user-state alignment, granting sovereign agency over all downstream actions. This neuro-symbolic architecture redefines the interface between human cognition and intelligent machines, enabling emotionally conscious, morally verifiable, and symbolically transparent AI governance in dynamic, high-stakes contexts.The present invention relates to artificial intelligence and neurotechnology, specifically to a real-time, neuro-symbolic operating system kernel that converts electroencephalography (EEG) signals into structured symbolic data for use in emotional cognition, ethical prioritization, autonomous agent dispatch, and real-time telecommunications routing. The invention bridges brain-computer interface (BCI) inputs with symbolic AI architectures to enable ethically aligned machine response during cognitively or emotionally intense events.

The disclosed technology includes a computer-implemented technique for generating images of physically producible products in response to user input describing a conceptual product. The system receives user input—such as natural language text, speech, or images—via a user interface, configures a prompt for a generative artificial intelligence (AI) system, and generates an image representing a version of the conceptual product with distinct physical attributes. Each version is associated with a unique identifier, enabling selection, modification, and purchase of the conceptual product. The system supports multiple product categories, including jewelry, home décor, and fashion, and extracts physical attributes to determine manufacturability and pricing. User feedback is incorporated to improve AI performance. The invention enables presentation of selectable product versions and initiates manufacturing processes based on user selections, supporting unstructured user input and multiple data modalities.

An XR system is provided. This system captures images including images of a first hand of a user and a second hand of the user using one or more cameras. The XR system generates cropped images using the images, each cropped image including a surface of the first hand. The XR system detects a hand touch of the surface of the hand by a digit of the second hand using the cropped images. The hand touch is used as an input into an XR user interface of the XR system. The surface of the hand can be palmar surface or a hand dorsal surface.

A social media platform provides a map-based graphical user interface (GUI) for accessing social media content submitted for public accessibility via the social media platform supported by the map-based GUI. The GUI includes a map providing interactive location-based searching functionality in that selection of a target location by the user in the GUI, such as by tapping or clicking at the target location, triggers a search for social media content having geo-tag data indicating geographic locations within a geographical search area centered on the target location. A search period for which content is returned is dynamically variable based on the duration for which the tap or click is held.

Described is a system for generation location visualization on a map interface by identifying a current location of a user that is initiating an interaction function of an interaction client; identifying a map corresponding to the current location of the user; identifying one or more map tiles associated with the map; receiving historical location data of the user that is associated with the current location of the user; converting the historical location data into an overall polygon that is comprised of a plurality of polygons based on the identified one or more map tiles; and displaying the map with the plurality of polygons on a user interface.

An apparatus an method for generating three-dimensional representations of serial sections, wherein the method includes creating a plurality of slide images using a slide scanner, the slide scanner comprising an image sensor and a stage, receiving, using at least a processor, the plurality of slide images from the slide scanner, extracting, using the at least a processor, a plurality of features from the plurality of serial slide section images using a feature extraction algorithm, registering, using the at least a processor, the plurality of serial slide section images as a function of the plurality of feature, generating, using the at least a processor, a three-dimensional (3D) stack view, wherein the 3D stack view comprises the plurality of serial slide section images, and displaying the 3D stack view through a display device.

An Adaptive Tangible User Interface (ATUI) for use in an extended reality environment in which tangible interfaces are composed in real time based on identified affordances of existing objects in the physical environment and the input tasks of a user. An extended reality system can be provided with instructions executable by one or more processors to perform processing including: generating a representation of the real-world environment within a field of view of the user; identifying physical objects within the real-world environment; generating a set of possible performable gestures afforded by available object affordance factors; determining potential input tasks; composing performable gestures for the potential input tasks; and selecting a physical object for use as an adaptive tangible user interface. Techniques for designing a virtual user interface, overlaying the virtual user interface on a selected ATUI physical object, and maintaining alignment of the virtual user interface, are also provided.

The present disclosure relates to systems, methods, and non-transitory computer readable media for utilizing a diffusion prior neural network for text guided digital image editing. For example, in one or more embodiments the disclosed systems utilize a text-image encoder to generate a base image embedding from the base digital image and an edit text embedding from edit text. Moreover, the disclosed systems utilize a diffusion prior neural network to generate a text-image embedding. In particular, the disclosed systems inject the base image embedding at a conceptual editing step of the diffusion prior neural network and condition a set of steps of the diffusion prior neural network after the conceptual editing step utilizing the edit text embedding. Furthermore, the disclosed systems utilize a diffusion neural network to create a modified digital image from the text-edited image embedding and the base image embedding.

A system can be used to generate interactive data visualizations and textual content. The system receives a layout of a content item. The content item can be a data visualization dashboard or an article. The system can generate a content structure tree based on the layout. The content structure tree represents hierarchical and semantic relationships between sections of the content item. The system can receive input adding content elements, such as data visualizations or textual paragraphs, to sections within the content item. The system can identify text roles for different sections based on the content structure tree and the content elements. The system can generate text suggestions for the content item based on the text roles. The system can also generate text content for a text suggestion using a large language model, display the generated text content within the content item, and iteratively refine the content item.

A computer-implemented method includes receiving a request for a type of output image and a prompt from a user that describes an output image. The method further includes selecting, based on the type of output image and the prompt, a machine-learning model from a set of machine-learning models. The method further includes providing the request and the prompt as input to the selected machine-learning model. The method further includes generating, by the selected machine-learning model, the output image that satisfies the request and the prompt.

A method, apparatus, non-transitory computer readable medium, and system for image processing include obtaining an input prompt including an image quality level and a description of an object, generating an image embedding based on the input prompt, where the image embedding represents the object and the image quality level in a vector space, and generating a synthetic image based on the image embedding, where the synthetic image depicts the object and has the image quality level.

A media application performs object recognition on an initial image to identify a set of objects in the initial image. The media application determines whether the initial image is an outdoor scene. Responsive to the initial image being an outdoor scene, the media application determining a sky segment from the initial image. The media application determines whether the initial image includes a subject that is human or animal. Responsive to the initial image including the subject, the media application determines a subject segment from the initial image. The media application receives at a user interface that includes the initial image, user input corresponding to selection of a selected object from the set of objects. The media application updates the user interface to include an indication that the selected object was selected.

To improve usability for obtaining content to be arranged in a product in an information processing apparatus for generating data of the product such as a poster.SOLUTION: The first prompt determined by the determining means when the receiving means has received a first target impression is different from the second prompt determined by the determining means when the receiving means has received a second target impression that is different from the first target impression. The information processor is provided with a receiving means that receives a user's designation of a target impression, which is an impression that the product is ultimately required to hold, and a determining means that determines a prompt for the generation AI to generate content to be arranged in the product.SELECTED DRAWING: Figure 2

An extended Reality (XR) system is provided for providing a user interface in an XR environment. The XR system detects a position and an orientation of a hand of a user. The XR system determines a user view of the hand using the detected position and orientation. In response to determining the user view is of a dorsal surface of the hand, the XR system causes display of a hand-centric user interface using a set of dorsal surface user interface elements. In response to determining the user view is of a palmar surface of the hand, the XR system causes display of the hand-centric user interface using a set of palmar user interface elements. The XR system detects, using the set of tracking sensors, a user input based on an interaction with the hand-centric user interface. The XR system then performs an action based on the detected user input.

Systems, methods, and non-transitory computer-readable media generate custom animations comprises a structure of a coarse animation prompt. For example, the disclosed systems receive a style prompt and receive a coarse animation prompt. The disclosed systems generate, utilizing a media generation model, a custom animation having a structure and timing of the coarse animation prompt and a style informed by the style prompt. The disclosed systems also provide the custom animation for display via a graphical user interface.

Systems and methods for fully automated anatomical analysis of an anatomical structure are provided to facilitate pre-operative planning. The computerized method may include obtaining a plurality of images, e.g., MSCT images, of patient-specific cardiovascular anatomy, and analyzing the MSCT images with a trained artificial intelligence module to identify one or more anatomical landmarks and to construct a virtual three-dimensional model of the anatomical structure. For example, the trained artificial intelligence module may execute segmentation, point detection, curve detection, or plane detection deep learning modules, independently or in combination, to identify the anatomical landmarks. The method further may include deriving anatomical measurements of the one or more identified anatomical landmarks, and displaying the virtual three-dimensional model alongside the anatomical measurements of the one or more identified anatomical landmarks.

To prevent reading errors of codes attached to workpieces being transported in logistics. A code reader system comprises: one or more sensors that detect a workpiece and measure dimensions of the workpiece; one or more cameras that capture at least one image of the workpiece; a decoding unit that performs decoding processing on at least one image; an output unit that outputs information indicating the reading stability for each surface of the workpiece using one or more cameras, based on installation information of the one or more sensors, installation information of the one or more cameras, conveying speed, and the workpiece dimensions; and a screen generation unit that generates a screen to display on a display device the results of the decoding processing of the code attached to the workpiece and information indicating the reading stability for each surface of the workpiece.

An eXtended reality (XR) system is provided that causes display of an interactive XR user interface of an XR application including an interactive virtual object. The XR system renders the interactive virtual object using a first set of interactive virtual object attributes and causes display of the interactive virtual object to a user as a component of the XR user interface. The XR system detects a pinch gesture of a hand of the user in proximity to the interactive virtual object and determines a set of pinch attributes of the pinch gesture. In response to detecting the pinch gesture, the XR system renders the interactive virtual object using a second set of interactive virtual object attributes based on the set of pinch attributes. The XR system then causes re-display of the interactive virtual object to the user and performs an action based on the set of pinch attributes.

An eXtended Reality (XR) system provides methodologies for clipping virtual content displayed to a user. The XR system generates an XR user interface with virtual content using an XR user interface model. The XR system generates clipped virtual content from the virtual content by clipping virtual content that is located outside of the user's stereoscopic field of view and provides the XR user interface containing the clipped virtual content to the user.

Systems and methods for image processing (e.g., image extension or image uncropping) using neural networks are described. One or more aspects include obtaining an image (e.g., a source image, a user provided image, etc.) having an initial aspect ratio, and identifying a target aspect ratio (e.g., via user input) that is different from the initial aspect ratio. The image may be positioned in an image frame having the target aspect ratio, where the image frame includes an image region containing the image and one or more extended regions outside the boundaries of the image. An extended image may be generated (e.g., using a generative neural network), where the extended image includes the image in the image region as well as generated image portions in the extended regions and the one or more generated image portions comprise an extension of a scene element depicted in the image.

Systems and methods for location-based device control are provided. Example systems and methods include determining a location estimate for a computing device and identifying a controllable device based on the location estimate. Some examples also include determining a relative location of the controllable device with respect to the computing device and triggering display, on the computing device, of a user interface for interacting with the controllable device based on the relative location. Another example system and method includes identifying a controllable device within a physical space based on an aiming direction in which a computing device is aimed, determining an angular offset of the controllable device with respect to the aiming direction of the computing device, and triggering display, on the computing device, of a user interface that indicates the determined angular offset.

Methods and systems are disclosed for applying augmented reality animations to an image. The methods and systems access an image and select an augmented reality (AR) experience to apply to the image, the AR experience comprising one or more AR element animations. The methods and systems repeatedly apply the AR experience to the image over a specified time interval to overlay the one or more AR element animations on the image. The methods and systems generate a video having a duration corresponding to the specified time interval in response to repeatedly applying the AR experience to the image, the video depicting the one or more AR element animations on the image.

Examples relate to systems and methods for generating digital effects experiences. The system performs operations including accessing a set of instructions that defines a digital effects experience. The system processes the set of instructions by a generative machine learning model to generate one or more digital effects comprising the digital effects experience. The system continuously processes one or more inputs, received by a user device, while the one or more digital effects comprising the digital effects experience are presented on the user device, along with the set of instructions in real time by the generative machine learning model to update presentation of the one or more digital effects comprising the digital effects experience.

Provided in the present disclosure are a virtual gift-based interaction method, and a related device. The method comprises: receiving a first image determined by a user in a virtual gift customized interface of a target livestream; in response to detection of a user instruction for transmitting a virtual gift, acquiring a second image corresponding to the target livestream; on the basis of the first image and the second image, generating a target virtual gift; and transmitting the target virtual gift to a livestream account associated with the target livestream.

An extended Reality (XR) system is provided for providing a user interface in an XR environment. The XR system detects a position and an orientation of a hand of a user. The XR system determines a user view of the hand using the detected position and orientation. In response to determining the user view is of a dorsal surface of the hand, the XR system causes display of a hand-centric user interface using a set of dorsal surface user interface elements. In response to determining the user view is of a palmar surface of the hand, the XR system causes display of the hand-centric user interface using a set of palmar user interface elements. The XR system detects, using the set of tracking sensors, a user input based on an interaction with the hand-centric user interface. The XR system then performs an action based on the detected user input.

A method for analyzing a feature of interest using a skin inspection system is disclosed. The method comprises generating a first output from a first machine learning model, which analyzes a current image dataset from a skin inspection device to determine a detected state of the feature on a user's skin. A second machine learning model generates a second output comprising a predicted state of the feature, based on historical data for that feature. A processor compares the first output (the detected state) with the second output (the predicted state) to determine a deviation. Finally, the determined deviation is classified into one of a plurality of predefined clinical risk categories.

A system for generating a customized design for a brand based on artificial intelligence makes it possible to learn a unique brand style for each brand and then automatically generate a user prompt based on a brand selected by a user, and automatically generate and suggest a new clothing image by comprehensively considering the selected brand, the user prompt, and trend data.

An apparatus method for leveraging a repository of images containing implant devices in a human body are disclosed. The apparatus includes at least a processor and a memory communicatively connected to the at least a processor, wherein the memory contains instructions configuring the at least a processor to receive a plurality of sets of historical subject data, classify the plurality of sets of historical subject data into one or more implant cohorts, receive an inquiry datum from a user, wherein the inquiry datum includes current subject data and generate an output datum as a function of the inquiry datum using an implant machine-learning model.