24428results about "Graph reading" patented technology

A system and method for creating complex, immersive, and interactive digital content is disclosed. The system integrates advanced artificial intelligence, multi-modal input processing, cloud-based shared environments, and immersive hardware to generate, optimize, and deliver rich interactive experiences. The platform supports content mashups, custom scenario generation, and adaptive AI behaviors, enabling the creation of unique and engaging digital environments across various media formats.

The method can include: recording a neural state, determining a latent array, and determining an output based on the latent array. In variants, the method can function to enable a subject to use neural signals to navigate within a high-dimensional concept space to control an output (e.g., image generation, motor control, communication, etc.).

The invention discloses a digital twin enabling intelligent pump station preventive operation and maintenance system. Comprising a dynamic twin construction module, a multi-source heterogeneous multi-modal data acquisition module, an edge computing and cloud collaboration module, an equipment health degree evaluation module, a predictive maintenance decision module, a cross-system data fusion module, a self-evolution knowledge graph module, an intelligent diagnosis and early warning module, a self-adaptive maintenance decision module and a man-machine collaboration interaction module. And the dynamic twin construction module comprises a physical-virtual synchronous calibration mechanism and an equipment degradation parameter dynamic updating mechanism. According to the method, the limitation problem of a traditional static model is solved, the method can adapt to nonlinear changes under complex working conditions, the comprehensive judgment and prediction capability of the system on the equipment state can be enhanced, the energy utilization efficiency is improved, the energy consumption is reduced, the decision and verification mechanism is perfected, and the data acquisition and processing problem is improved; the problems of timeliness and flexibility of the model are solved, and the computing architecture and the response capability are optimized.

Methods for displaying and organizing user interfaces in a computer-generated environment provide for an efficient and intuitive user experience. In some embodiments, user interfaces can be grouped together into a container. In some embodiments, user interfaces can be added to a container, removed from a container, or moved from one location in the container to another location. In some embodiments, a visual indication is displayed before a user interface is added to a container. In some embodiments, a user interface can replace an existing user interface in a container. In some embodiments, when moving a user interface in a computer-generated environment, the transparency of a user interface that is obscured can be modified.

The method can include: recording a neural state, determining a latent array, and determining an output based on the latent array. In variants, the method can function to enable a subject to use neural signals to navigate within a high-dimensional concept space to control an output (e.g., image generation, motor control, communication, etc.).

Methods for counter-scaling windows and rearranging objects within those counter-scaled windows in a 3D computer-generated environment is disclosed. The windows can be counter-scaled in accordance with changes to their depth within the 3D computer-generated environment. Objects within the window can be presented at their actual size and with their correct scale relative to each other and with respect to the 3D computer-generated environment, and can maintain their actual size and scale relative to each other and the environment regardless of the depth of the window in the environment. Some embodiments of the disclosure rearrange the layout of the objects to present more or fewer objects in the window as the size of the window changes due to counter-scaling. Depth-dependent window resizing and object rearrangement while preserving actual object size and scale within the 3D computer-generated environment can provide a more authentic viewing experience and can encourage increased user interaction.

In some embodiments, an electronic device navigates between user interfaces based at least on detecting a gaze of the user. In some embodiments, an electronic device enhances interactions with control elements of user interfaces. In some embodiments, an electronic device scrolls representations of categories and subcategories in a coordinated manner. In some embodiments, an electronic device navigates back from user interfaces having different levels of immersion in different ways.

In some embodiments, a computer system displays a user interface element corresponding to content shared with the computer system for interacting with the shared content in the three-dimensional environment. In some embodiments, a computer system displays one or more virtual control elements in a three-dimensional environment that are selectable to cause one or more corresponding operations involving a physical device to be performed.

A holographic augmented reality ultrasound needle guide system and method includes an augmented reality display such as a headset wearable by a user. The augmented reality display is configured to depict a virtual ultrasound image. The augmented reality display is further configured to allow a user to select a desired reference point on the virtual ultrasound image. The system is configured to depict a holographic needle guide based on the selection of the desired reference point. The system is also configured to adjust a trajectory of the holographic needle guide to avoid intersecting undesired anatomical structures. The augmented reality display is further configured to stamp the holographic needle guide into a selectively locked trajectory and position.

The invention discloses a community intelligent monitoring and emergency linkage method and system fusing BIM spatial semantics, and the method comprises the steps: constructing a BIM scene map, and obtaining the attributes and mutual relationships of components and spatial regions in a BIM model; mapping a dynamic target detected in video monitoring into the BIM model, and obtaining spatial semantic information of the dynamic target; based on BIM spatial semantic information of a dynamic target, a target-environment interaction graph is constructed, a graph neural network model is used for training and reasoning, and specific complex events related to spatial contexts are recognized; taking the BIM model as a space-time reference, fusing multi-source heterogeneous data, and reconstructing by adopting a graph-based event association algorithm to form a complete event chain containing an atomic event sequence and an association relationship; and when an emergency event or an event chain is detected to indicate an emergency state, combining BIM preset information and real-time sensor data, dynamically generating an optimal emergency plan, and performing visual commanding and dispatching through a BIM three-dimensional scene and augmented reality.

The invention relates to the technical field of artificial intelligence assisted medical rehabilitation, in particular to a peripheral nerve injury personalized rehabilitation system and method based on a multi-modal large model, and the method comprises the steps: a feature fusion module employs space-time attention to fuse multi-modal time series data, and constructs an evaluation map; the personalized generation module is combined with historical data and reinforcement learning to generate a scheme containing virtual scene parameters; the interaction feedback module collects data through mixed reality and calculates action deviation; and the adaptive adjustment module adopts a meta-learning optimization model and a distributed iterative output scheme. According to the method, the cross-modal association precision of the motion features and the mechanical parameters is improved, dynamic matching of the training scene and the motion ability of the user is achieved, the virtual environment and the mechanical feedback threshold are optimized by dynamically adjusting the rehabilitation scheme parameters, the scheme optimization period is shortened based on an online iterative optimization mechanism, and the training efficiency is improved. The core defects of personalized adaptation lagging and low utilization efficiency of multi-modal data are overcome.

The invention discloses a robot anthropomorphic interaction method based on multi-modal emotion recognition and customized portrait generation. The method comprises the following steps: S1, dynamically fusing multi-modal emotions; the method comprises the following steps: S1, synchronously acquiring voice, visual and text signals through a multi-source heterogeneous sensor, capturing a user voice stream by a high-fidelity microphone array, and extracting acoustic characteristics such as intonation and speed, S2, performing cross-modal reasoning; s3, synchronously generating contents; step S4: style migration; step S5, anthropomorphic voice and expression generation; according to the method, man-machine interaction emotion is analyzed and generated by utilizing a large language model and multi-modal information fusion, the singleness of interaction emotion and the deficiency of emotional sharing ability are avoided, a strong emotion interaction characteristic is achieved, the image of the robot is obtained through a generative technology and can be migrated to any image, the limitation that a specific image is independently made is broken through, and the interaction effect of the robot is improved. The advantage that one robot can be suitable for different scenes is achieved.

The invention discloses an AR navigation system and method based on a visual language model, and the method comprises the steps: firstly carrying out video data collection, and constructing a memory database; secondly, querying a navigation target most related to a natural language request of a user in the constructed memory database to obtain a current AR equipment pose and a target pose; and then solving the shortest path from the current pose to the target pose by using the current AR equipment pose and the target pose according to the point cloud map, and optimizing the path direction to finally obtain an optimized path. And finally, guiding a user to move along the planned path through view superposition path indication and voice prompt in AR equipment by utilizing the optimized path, and updating the point cloud map and the memory database. According to the invention, high-precision real-time positioning and sparse point cloud map construction can be realized only by camera input in indoor and outdoor complex environments with low GPS precision, accurate navigation is carried out, and the flexibility and intelligent level of navigation are improved.

The invention discloses a medical whole-course intelligent management system based on a large model, and belongs to the technical field of large models. Comprising a multi-modal data acquisition module, a privacy calculation preprocessing module, a dynamic knowledge enhancement module, a time sequence data analysis module, an intelligent decision engine module, a multidisciplinary collaboration module, a patient interaction platform module, a dynamic intervention feedback module and a system security center module. The cross-mechanism data security sharing is realized, and the compliance of sensitive information processing is also ensured; a two-channel medical knowledge base is constructed, authoritative guidelines can be synchronized, newest clinical research data can be analyzed in real time, the knowledge base is kept in the newest state all the time, and the frontier scientific basis is provided for clinical decisions; dynamic modeling and trend prediction are carried out on long-term monitoring data of a patient by adopting a hybrid neural network model, and potential health risks and development trends can be identified more accurately.

In some embodiments, while displaying a content entry user interface element and while a first content entry tool is selected, an electronic device detects a first movement of a predefined portion of a user while the predefined portion has a first shape. In some embodiments, in response to detecting the first movement, in accordance with a determination that a gaze of the user was directed toward the content entry user interface element when the first movement was detected, the electronic device enters first content, based on the first content entry tool, corresponding to the first movement into the content entry user interface element. In some embodiments, in accordance with a determination that the gaze of the user was directed toward a menu user interface element when the first movement was detected, the electronic device selects a second content entry tool for entering content into the content entry user interface element.

The invention discloses a dynamic interaction method based on cooperation of a multi-modal dynamic fusion large model and an intelligent agent. The method comprises the following steps: performing feature extraction on user voice information to obtain a voice coding vector, a text semantic vector and an emotion feature vector; performing dynamic weight feature fusion on the voice coding vector, the text semantic vector and the emotion feature vector through a multi-modal dynamic fusion large model to obtain a fusion feature vector; inputting the fusion feature vector into an intention-scene coupling network, and identifying to obtain a user intention label; and identifying according to the user behavior log to obtain a user portrait tag, inputting the user intention tag and the user portrait tag into an autonomous decision-making agent, generating a target decision-making action through a lightweight policy network, and then interacting with the user according to the target decision-making action. The intelligent interaction efficiency and accuracy of the customer service system are improved, the interaction experience of the user is also improved, and the method can be widely applied to the technical field of artificial intelligence.

The invention relates to the technical field of flight training evaluation, and discloses an electroencephalogram feature and physiological index fused flight training evaluation system. The system comprises a physiological signal acquisition module which synchronously captures multichannel electroencephalogram original signals and body surface physiological index data, and the body surface physiological index data comprises an electrocardiograph R-R interval sequence, respiratory wave frequency amplitude and galvanic skin response amplitude; the multi-modal fusion module is used for analyzing an electrocardiograph R-R interval sequence to generate a heart rate variability feature vector and establishing dynamic association mapping of an electroencephalogram entropy value and a physiological feature vector; the cognitive state modeling module is used for generating a cognitive load index according to the dynamic association mapping and constructing a cognitive stability quantization matrix; the self-adaptive feedback module is used for receiving related data and dynamically adjusting simulated flight scene parameters; and the evaluation output module is used for integrating the data to generate a comprehensive training evaluation report containing a neurophysiological coordination degree score and an operation accuracy rating. According to the system, comprehensive evaluation and dynamic training adjustment of the cognitive state of the pilot are realized.

The invention belongs to the technical field of robot control, particularly provides a force feedback teleoperation control system and method for the tail end of a mechanical arm of a quadruped robot, and aims at the key challenges that control errors are caused by communication time delay and soft obstacles are difficult to recognize in a dynamic environment. Modeling and judgment are conducted on the contact state of the tail end of the mechanical arm in advance, and feedforward control and buffer adjustment oriented to communication time delay are achieved. And meanwhile, a dynamic semantic map is constructed in combination with multi-source sensing information, and soft obstacle reasoning and path optimization are performed by fusing a tail end force sense change trend, so that the recognition and avoidance capabilities of the system in a complex and invisible obstacle environment are remarkably improved. The system has good perspectiveness, self-adaptability and high redundancy safety characteristics, is suitable for multi-task inspection operation of industrial sites such as a thermal power plant, and is especially suitable for a remote man-machine cooperative operation scene in a narrow space.

The invention relates to the field of virtual reality positioning, and discloses a VR large-space positioning interaction system based on multi-modal perception, and the system comprises the steps: deploying a multi-modal sensor to obtain sensing data, carrying out the visual feature extraction and preprocessing, building a sparse point cloud map in a matching manner, carrying out the scale calibration, and constructing an environment model; pre-judging a UWB signal path based on an environment model, performing error optimization compensation on an NLOS state, and performing observation updating and fusion through degradation detection to obtain a predicted state change; constructing an interactive perception network, and tracking the hands and the whole body; tactile feedback is realized by using a layered tactile system, and a tactile effect is generated by using vibration frequency mapping; the transmission efficiency is improved by using a beam forming technology, an edge cloud server cluster renders a virtual scene, and the scene is pre-rendered in advance to offset network and rendering delay; an online calibration mechanism is designed, and system errors are corrected through visual loopback detection, UWB beacon dynamic correction and IMU drift compensation.

Methods for displaying user interfaces in a computer-generated environment provide for an efficient and intuitive user experience. In some embodiments, user interfaces can have different immersion levels. In some embodiments, a user interface can have a respective immersion level based on its location in the three-dimensional environment or distance from the user. In some embodiments, a user interface can have a respective immersion level based on the state of the user interface. In some embodiments, a user interface can switch from one immersion level to another in response to the user's interaction with the user interface.

The invention relates to the technical field of press monitoring, in particular to a digital twinning-based three-dimensional monitoring system for a precision servo press, which comprises a physical layer sensing module for acquiring real-time operating parameters, environment variables and workpiece processing data of the press; the dynamic twin construction module constructs a total-factor digital twin, and simulates a force-heat-deformation coupling effect by using finite element analysis and a multi-body dynamics algorithm based on physical attributes and process parameters; the intelligent analysis center identifies a potential fault mode of the press machine and locates an abnormal source through multi-physics field simulation data in combination with an improved CNN-LSTM model; the three-dimensional visual interaction unit constructs an interactive immersive three-dimensional virtual scene, renders a running state and a processing process in real time, and generates a maintenance strategy; and the self-adaptive regulation and control unit predicts the residual life of the key component and dynamically adjusts parameters according to a maintenance strategy and real-time monitoring data. Therefore, the problems of single monitoring dimension, disjunction of maintenance strategies and the like in the prior art are solved.

The invention discloses a BIM (Building Information Modeling)-based hoisting construction safety monitoring and early warning system. The system comprises a terminal sensing layer which is used for collecting environmental parameters and personnel behavior data in a closed space in real time; the edge computing layer is used for carrying out cleaning, compression and encrypted transmission on original data by utilizing an explosion-proof edge computing gateway; the cloud collaboration layer is used for storing full data based on a BIM digital twinborn platform, constructing a'danger mode-construction feature-disposal measure 'three-dimensional meta-knowledge graph by adopting an MAML + + algorithm, meanwhile, coupling a physical mechanism data enhancement engine with a multi-physics field coupling model and a physical constraint generative adversarial network, generating virtual data conforming to mass conservation and energy conservation, and sending the virtual data to the cloud collaboration layer; performing mixed training with real data; according to the intelligent decision-making layer, a space-time adaptive threshold evolutionary algorithm encodes a space-time context through a graph attention network and Transform, an alarm threshold is dynamically optimized through deep reinforcement learning, meanwhile, a digital twin deduction engine calculates a shortest safety path in real time, and rescue resource allocation is optimized.

The invention provides a smart glasses AI voice interaction method, which comprises the following steps: simultaneously acquiring a user gesture image and a voice signal, acquiring a user historical interaction record, extracting key point coordinates and pointing direction information of the gesture image, acquiring hand distance information, generating a gesture motion path, simultaneously extracting frequency spectrum information and an intonation peak value of the voice signal, and generating a gesture motion path; forming a voice beat sequence; extracting a spatial semantic mode of the gesture and voice fusion data, and recognizing a core object of a user pointing instruction according to pointing coordinates of a gesture motion path and an intonation peak value of a voice beat sequence; after the core object pointing to the instruction is recognized, the user intention is determined in combination with the spatial semantic mode and the historical interaction record of the user; and the complete intention analysis result is output to the intelligent glasses display module to execute corresponding operation, and is fed back to the acquisition module to adjust the next capture parameters including the acquisition frequency and the recognition sensitivity, so that the response speed and the accuracy are improved.

The invention discloses an AR home experience method in a large scene. On the basis of combination of a natural feature identification-based three-dimensional registration method and a binocular tracking positioning and local mapping method, the camera attitude is estimated by using feature points of a real-time scene and corresponding three-dimensional points thereof under the binocular trackingpositioning and local map construction technology. According to the mode, on-site environment features shot in real time are used as recognition tracking objects, a virtual home model can still be normally positioned and tracked under the condition that no identification graph exists, the problems that an existing AR home experience application is small in use range and poor in stability are solved, and therefore the AR home experience of virtual and real fusion can be met in a wider range and more truly.

The invention relates to the field of building intellectualization, in particular to a digital twinborn mixed cloud edge collaborative intelligent house building group operation and maintenance intelligent system, which establishes a digital twinborn scene database by collecting building basic information, equipment operation data and environmental parameters, synchronizes the digital twinborn scene database to edge equipment, and uses BIM, GIS, Internet of Things, 5G and AI technologies to establish a digital twinborn scene database, so as to realize the intelligent operation and maintenance of a building group. A virtual-real combined digital intelligent building scene is constructed, real-time synchronization of a virtual scene and a physical environment is realized through AR / VR equipment, and an operation and maintenance module comprises multi-source heterogeneous data fusion, edge intelligent analysis decision, adaptive model training and iterative optimization, a predictive maintenance algorithm of virtual-real mapping and a multi-level collaborative decision and autonomous scheduling mechanism. And the monitoring module monitors the state and operation condition of the edge equipment, provides data service and supports visualization of management decisions, and the system effectively improves the intelligence and digitization level of operation and maintenance of the building group.

In some embodiments, an electronic device emphasizes and / or deemphasizes user interfaces based on the gaze of a user. In some embodiments, an electronic device defines levels of immersion for different user interfaces independently of one another. In some embodiments, an electronic device resumes display of a user interface at a previously-displayed level of immersion after (e.g., temporarily) reducing the level of immersion associated with the user interface. In some embodiments, an electronic device allows objects, people, and / or portions of an environment to be visible through a user interface displayed by the electronic device. In some embodiments, an electronic device reduces the level of immersion associated with a user interface based on characteristics of the electronic device and / or physical environment of the electronic device.

The invention provides a game cartoon character display method based on a virtual reality technology. The method comprises the following steps: acquiring three-dimensional model data of a game cartoon character in a target display area through a user interaction terminal; the virtual reality content management platform determines a dynamic rendering precision level according to the model data, and generates a real-time rendering strategy including a model patch reduction coefficient, a texture compression rate and a skeleton animation updating frequency in combination with terminal performance parameters; the strategy is sent to a virtual reality supervision platform and a user interaction terminal, and a virtual reality rendering engine platform is instructed to execute real-time rendering; and the virtual reality supervision platform monitors the frame rate fluctuation data of the head-mounted display device, calculates the scene rendering stability, sends a rendering optimization instruction if the scene rendering stability is lower than a threshold value, and adjusts the model data acquisition frequency and the video memory cleaning period to optimize the performance. The rendering efficiency and the system stability can be improved, and the hardware load and the frame rate fluctuation are reduced.

The invention relates to the field of multi-modal interaction analysis, in particular to a multi-modal interaction method and system of a digital human agent. The method comprises the following steps: acquiring a real-time face image and a voice signal input stream of an interactive user based on an intelligent agent; performing real-time micro-expression recognition and deep emotion analysis based on the real-time facial image to obtain real-time emotion features of the user; performing time sequence evolution analysis on the real-time emotion characteristics of the user, performing holographic user emotion deep mining, and constructing a user emotion holographic characteristic spectrum; carrying out adaptive acoustic gain processing on the voice signal input stream, and carrying out voice-emotion association analysis based on the user emotion holographic characteristic spectrum to generate a voice-emotion linkage mapping spectrum; and carrying out eyeball fixation point migration tracking based on the user emotion holographic feature map and the real-time face image, and generating a user interaction depth intention signal. Through the real-time deep semantic understanding and emotion perception ability, the intelligent agent interaction intelligence and response accuracy are improved.

The invention relates to the technical field of intelligent interaction systems, and discloses an intelligent interaction system and method based on a multi-modal large model. The system comprises a multi-modal input layer, a context sensing module, a cross-modal fusion module, a dynamic response generation module and a system monitoring module. The multi-modal input layer preprocesses multi-modal data; the context sensing module constructs a dynamic context vector; the cross-modal fusion module fuses the data to generate joint features; the dynamic response generation module generates a response strategy through hierarchical decision; and the system monitoring module monitors the key indexes and triggers an optimization mechanism. All the modules work cooperatively, multi-modal data deep fusion, precise context sensing, efficient dynamic response and system self-optimization are achieved, the accuracy, adaptability and stability of intelligent interaction are improved, and the method can be widely applied to multiple fields such as intelligent home and intelligent customer service.