5372results about "Television systems" patented technology

Systems and methods for integrating generative artificial intelligence (AI) capabilities within Software as a Service (SaaS) platforms. One of the computer-implemented methods are for querying a generative AI model about structured data in a SaaS environment, enabling users to interact with and manipulate data through AI-assisted interfaces. One of the systems maintains a generative AI agent configured to interact with SaaS platform data as a virtual team member, capable of understanding context and nuances of project data. Also described are methods for color-context aware data analysis, generation of interactive elements in messaging sessions, and cross-application generative AI agent interactions triggered by user mentions. Also described is facilitating the creation of custom SaaS platform products by combining functionalities from existing products using generative AI. The systems and methods represent advancement in AI-driven SaaS customization and data analysis.

The invention relates to methods and systems for integrating generative artificial intelligence (AI) capabilities into Software as a Service (SaaS) platforms. It comprises maintaining AI agents with varying credentials, enabling their interaction with alphanumeric data in table structures, and implementing a hierarchical access control scheme. The system displays table structures, provides interfaces for user inputs, and allows AI agents to be added as platform users. The generative AI agents can analyze data, identify actions, and perform tasks autonomously. The invention also includes methods for proactive information gathering, interactive analysis of AI outputs, and management of AI resources as limited assets. This approach enhances SaaS functionality by enabling AI-driven task completion, data analysis, and decision-making while maintaining data security and user-specific access controls.

Systems, methods, and apparatus for detecting UAVs in an RF environment are disclosed. An apparatus is constructed and configured for network communication with at least one camera. The at least one camera captures images of the RF environment and transmits video data to the apparatus. The apparatus receives RF data and generates FFT data based on the RF data, identifies at least one signal based on a first derivative and a second derivative of the FFT data, measures a direction from which the at least one signal is transmitted, analyzes the video data. The apparatus then identifies at least one UAV to which the at least one signal is related based on the analyzed video data, the RF data, and the direction from which the at least one signal is transmitted, and controls the at least one camera based on the analyzed video data.

Systems, methods, and apparatus for detecting UAVs in an RF environment are disclosed. An apparatus is constructed and configured for network communication with at least one camera. The at least one camera captures images of the RF environment and transmits video data to the apparatus. The apparatus receives RF data and generates FFT data based on the RF data, identifies at least one signal based on a first derivative and a second derivative of the FFT data, measures a direction from which the at least one signal is transmitted, analyzes the video data. The apparatus then identifies at least one UAV to which the at least one signal is related based on the analyzed video data, the RF data, and the direction from which the at least one signal is transmitted, and controls the at least one camera based on the analyzed video data.

A method for autonomous fault detection, identification and healing of a smart vision device is provided. A first data corresponding to the smart vision device is generated and acquired in real time. The first data is operation status data of components of the smart vision device. The first data is processed through time-series analysis to generate a second data corresponding to the first data. The second data is abnormal data in the operation status data. A self-healing mechanism corresponding to the smart vision device is constructed. Based on the self-healing mechanism and a fault type of the second data, the smart vision device is autonomously healed in real time. A system and platform for implementing the method are also provided.

This document relates to providing adaptive teleconferencing experiences using generative image models. For example, the disclosed implementations can employ inpainting and / or image-to-image restyling modes of a generative image model to generate images for a teleconference. The images can be generated based on prompts relating to the teleconference. Users can be superimposed on the generated images, thus giving the appearance that the users are present in an environment generated by the generative image model.

A security device maintenance system is provided. The aspects include one or more processors configured to assess security data quality by conducting one or more tests that compare the security data to one or more predetermined thresholds, assign one or more anomaly indicators to security devices if the security data quality fails to meet the one or more predetermined thresholds, and generate an automated maintenance report for the one or more security devices including the one or more anomaly indicators. The aspects can also include periodically retrieving one or more security data from the one or more security devices, utilizing an artificial intelligence (AI) model to detect one or more anomalies, and generating one or more predictive maintenance suggestions.

A computing system displays, via a first display generation component, a first computer-generated environment and concurrently displays, via a second display generation component: a visual representation of a portion of a user of the computing system who is in a position to view the first computer-generated environment via the first display generation component, and one or more graphical elements that provide a visual indication of content in the first computer-generated environment. The computing system changes the visual representation of the portion of the user to represent changes in an appearance of the user over a respective period of time and changes the one or more graphical elements to represent changes in the first computer-generated environment over the respective period of time.

A computer system implements a 3D virtual environment (312) configured to be accessed by a plurality of client devices each having corresponding a user graphical representation (322) within the 3D virtual environment, which includes positions for the user graphical representations (322) arranged in a geometry (330) and a virtual camera (314) positioned within the 3D virtual environment. The virtual camera (314) moves on a predetermined path (332) that maintains a distance between the virtual camera (314) and the positions (322) arranged in the geometry for the user graphical representations. The computer system captures a video stream from the perspective of the virtual camera on the predetermined path. The video stream includes video of the user graphical representations in the positions arranged in the geometry. The predetermined path maintains a constant viewing orientation angle between the virtual camera and the positions arranged in the geometry, which may include predefined seating positions at a virtual conference table.

The invention relates to the field of image signal processing, in particular to a household camera imaging quality detection method and system. Comprising the following steps: acquiring a to-be-detected image sequence shot by a camera in a preset scene; carrying out regional preprocessing on the to-be-detected image sequence; extracting motion feature parameters of a dynamic target area and static feature parameters of a static background area in the preprocessed to-be-detected image sequence; inputting the motion characteristic parameters and the static characteristic parameters into a preset imaging quality evaluation model, and outputting a comprehensive quality score; and obtaining an imaging quality grade of the camera based on a comparison result of the comprehensive quality score and a preset threshold value. According to the invention, by constructing the preset scene including the dynamic target area and the static background area, the composite environment of the household scene is accurately simulated; meanwhile, illumination gradient change control is introduced, a typical household illumination range is covered, and the problem of detection distortion caused by a single scene in an existing method is solved.

The invention provides a video quality detection method based on multi-scene self-adaption. The method comprises the following steps: selecting an area in a video picture, extracting multi-dimensional features of the area, determining the type of a scene where the video picture is located, and dynamically adjusting video detection parameters of the video picture; detecting the quality of the video picture based on the video detection parameters; intercepting an abnormal video picture, and adding the abnormal video picture into the constructed equipment fault template library M; and performing local model retraining on the video quality detection model based on the equipment fault template library M, and detecting the quality of a to-be-detected video picture based on the video quality detection model. On the basis of deep analysis of different scene features, the scene type of the video picture is accurately judged through multi-dimensional feature calculation, and then the video quality detection parameters are dynamically adjusted according to the scene type, so that the detection system can automatically adapt to the optimal detection parameters according to scene changes, misjudgment and missed judgment caused by the scene changes are avoided, and the detection efficiency is improved. And the accuracy of video quality detection in different scenes is remarkably improved.

An example method for AI-assisted notifications of relevant content during a virtual conference includes joining, by a client device, a virtual conference attended by one or more participants using a client application. For example, the client device may receive, a transcript of the virtual conference from a server during the virtual conference and determine if the transcript includes a phrase associated with the participant. In response to determining that the transcript includes the phrase associated with the participant, outputting a notification to the participant on a graphical user interface (GUI) provided by the client application.

A computing system displays, via a first display generation component, a computer-generated environment, and concurrently displays status information corresponding to the computing system via the second display generation component, including concurrently displaying: a visual representation of a portion of a user of the computing system who is in a position to view the computer-generated environment via the first display generation component, and one or more graphical elements that provide a visual indication of content in the computer-generated environment. The computing system detects a respective event; and in response, the computing system changes a level of immersion of the computer-generated environment displayed via the first display generation component, and changes the status information that is displayed via the second display generation component, including changing an appearance of the visual representation of the portion of the user of the computing system.

Systems and methods for providing one-to-one and audio and video calls or for providing multi-party audio or video conferences also provide language translation services. When language translation services are provided, a party to a call or conference hears both the audio of the speaker, and a translated version of the speaker's audio.

A method of calibrating multiple cameras includes determining a first position of an overlay within a first field of view of a first camera and a second position of the overlay within a second field of view of a second camera; selecting, from the first camera and the second camera based on the first position and the second position, the first camera as a presentation camera; presenting, on a display, an image of a calibration object captured by the presentation camera and the overlay, the overlay indicating a calibration position for the calibration object with respect to the presentation camera; capturing a first calibration image of the calibration object by the first camera and a second calibration image of the calibration object by the second camera; and calibrating the first camera based on the first calibration image and calibrating the second camera based on the second calibration image.

Described herein are techniques for generating contextually rich plant images. A number of data captures of raw plant data are generated via a sensing unit configured to navigate a growing facility. Metadata is generated and assigned to the raw plant data including at least one of: plant location, timestamp, plant identification, plant strain, facility identification, facility location, facility type, health risk factors, plant conditions, and human observations. Images generated by the sensing unit are analyzed and pixel annotations are generated in the images based on their relation to one or more plant well-being features. Data tags are generated and assigned the data captures based on an analysis of the data captures. The data tags are text phrases linking a particular data capture to a specific threat to plant well-being.

The invention discloses an optical imaging zoom point selection correction method and system, which can correct the deviation between a theoretical model and actual lens characteristics in real time through a peak point tracking algorithm and offset vector calculation in a second stage, effectively solve the problem of individualized errors caused by lens group assembly tolerance, material refractive index difference and the like, and improve the correction accuracy. The stratified sampling strategy of the first stage is combined with the slope interpolation of the third stage, untested points in a theoretical curve are filled, a high-precision focusing curve is generated, the full range of zooming is covered, and local focusing failure caused by traditional uniform sampling is avoided; according to the method, curve jitter caused by test noise or mechanical vibration is eliminated, a smooth zoom focusing curve is output, the anti-interference capability in actual control is improved, frequent jitter of a focusing motor is avoided, a search strategy is dynamically adjusted in combination with definition data, an actual peak point is quickly locked, and the problem of overmodulation or slow convergence caused by a traditional fixed step length is solved.

The invention relates to the technical field of image acquisition and testing, and discloses an image acquisition and testing method, device and equipment and a storage medium, and the method comprises the steps: collecting a standard test card image through an image acquisition card in a multi-stage standard illumination environment, and calculating sensitivity benchmark test data; executing time domain and space domain combined sampling processing to obtain super-sensitivity image data; performing brightness analysis and dynamic adjustment on the currently shot first scene image to obtain a first image acquisition parameter; acquiring a second scene image, and performing image grid division and contrast compensation on the second scene image to obtain an enhanced image after contrast compensation; according to the super-sensitivity image acquisition method and the super-sensitivity image acquisition device, the sensitivity limitation of the position depth of a traditional image acquisition card is broken through, and super-sensitivity image acquisition is realized.

The invention provides a crane remote control image delay detection method and system, and relates to the technical field of cranes, and the method comprises the following steps: carrying out space-time segmentation by using a dual-channel parallel preprocessing mechanism; acquiring three-dimensional space coordinates and motion parameters of the crane by utilizing an attention mechanism; calculating a motion state vector, inputting the motion state vector into the multi-modal deep learning model, and generating a video stream delay prediction curve; based on a prediction curve and a model prediction control algorithm, optimizing key frame distribution and coding parameters of the video stream, and transmitting the key frame distribution and coding parameters to a remote control terminal through an intelligent routing mechanism; modeling by adopting a recursive least square algorithm to obtain a probability distribution model; and generating a delay compensation control strategy through a hierarchical reinforcement learning algorithm, and carrying out adaptive time compensation on the operation instruction. According to the invention, the remote control image transmission delay is effectively reduced, and the real-time performance and safety of remote operation are improved.

A signal processing apparatus is provided which adds AI processing functions to an imaging system without such functions while improving the degree of freedom of AI processing that can be implemented by the imaging system.A signal processing apparatus according to the present technology includes an AI processing part configured to perform AI processing on an input image by using an AI model, an image processing part capable of selectively acquiring a different type of image as an image based on a captured image input from an outside, a control part configured to control settings of the image processing part on the basis of image designation data for designating an image to be obtained by the image processing part, and to control settings of the AI model for the AI processing part on the basis of AI model designation data for designating an AI model to be set to the AI processing part, and a transmission part configured to transmit information indicative of a result of the AI processing performed by the AI processing part to the outside.

The invention relates to the technical field of data processing, and discloses a film and television supervision analysis method and system based on data mining and a storage medium. The method comprises the following steps: collecting film and television data in a panoramic manner, and carrying out cross-media transcoding processing to obtain a multi-dimensional data set; performing video semantic extraction, audio emotion recognition and text tendency analysis on the data set to generate a time sequence mark list; scoring the key elements according to social influence, propagation depth and audience acceptability to form a dynamic score table; analyzing the propagation path based on the score table, and constructing an influence map; sorting supervision points according to the atlas, and making an intelligent supervision scheme; the execution deviation is analyzed through effect feedback, and the supervision parameters are optimized. According to the method, multi-dimensional content feature extraction, social influence evaluation and propagation path analysis of the film and television works are realized in a mass multimedia content environment, a precise and differentiated intelligent supervision scheme is formed, and the method has self-optimization and adjustment capabilities at the same time.

The invention discloses a noise suppression optimization method for a high-sensitivity camera module. The method comprises the following steps: S1, acquiring an original image and preprocessing the original image; s2, executing discrete Fourier transform, and converting the image into a frequency domain image; s3, inputting the frequency domain image into a Fourier neural operator model, and extracting frequency domain features; s4, inverse Fourier transform is executed, and a preliminary noise reduction image is generated to serve as a reference image; s5, adopting an improved jellyfish group optimization algorithm to perform global search and optimization on model structure parameters and hyper-parameters; s6, updating the Fourier neural operator model according to an optimization result, and performing closed-loop iterative optimization; and S7, performing image quality evaluation on the noise-reduced image and the reference image until performance indexes are met. According to the method, the Fourier neural operator and the improved jellyfish group optimization algorithm are fused, so that efficient noise suppression and image quality improvement of the high-sensitivity camera module in a low-light environment are realized.

Methods, systems, and apparatus, including medium-encoded computer program products, for computer aided design of physical structures include: rendering, to a display device of a first user, a first user's view into an extended reality environment, the first user's view being generated using a first pose being tracked for the first user; identifying that a first avatar associated with the first user has entered a shared perspective mode with a second avatar associated with a second user of the XR environment, wherein the shared perspective mode has a single frame of reference in the XR environment that is shared by the first user and the second user; and performing, while in the shared perspective mode, the rendering to the display device of the first user.

There is disclosed a system that, when in operation, encodes an input signal provided to an encoder to provide corresponding encoded data, wherein the encoded data is communicated via a data communication network to at least one decoder that decodes the encoded data to regenerate a rendition of the input signal that is output from the at least one decoder; the system is characterized in that the encoder computes and encodes at least one portion or at least one lower resolution layer of the encoded data and communicates the at least one portion or at least one lower resolution layer to the decoder concurrently as the encoder computes and encodes at least one other portion or at least one higher resolution layer of the encoded data for later communication to the at least one decoder, so that the encoder and the at least one decoder function temporally concurrently when processing a given image frame included in the input signal.

Methods and systems for determining whether a camera of an autonomous vehicle (AV) is calibrated are disclosed. The method includes using image frames captured by a camera of the AV and LIDAR point clouds captured by a LIDAR system of the AV to calculate an AV pose calibration metric. The method also includes: measuring a distance metric between a three-dimensional bounding box around an object and a two-dimensional bounding box in an image captured by the camera; using the AV pose calibration metric and the distance calibration metric to generate a confidence score; and in response to the confidence score being below a threshold, generating a signal indicating that the camera is not calibrated.

A row driver assembly includes a row driver unit. The row driver unit includes a buffer circuit that drives a control signal to a pixel circuit. The buffer circuit is electrically connected to a high buffer supply voltage and to a low buffer supply voltage. A voltage converter circuit supplies the low buffer supply voltage to the buffer circuit. An error detection circuit outputs an active error signal when the low buffer supply voltage is outside a target voltage window.

The invention discloses a large-scale video access and AI reasoning enhancement system and method, belongs to the technical field of video processing, and aims to solve the technical problem of how to realize large-scale video stream efficient access, resource elastic scheduling and abnormity self-healing in a complex environment. Comprising a resource dynamic scheduling module, a decoding and reasoning control module, a resolution dynamic processing module, a multi-stage shared memory transmission module, an exception self-healing and fault-tolerant module and a task parallel execution module, and resource allocation is optimized and calculated by dynamically binding a CPU core and GPU hardware unit isolation; the resolution is dynamically adjusted based on the scene algorithm precision requirement, and invalid calculation is reduced; a stream pushing and frame rate decoding strategy is controlled by using a Redis mark, and memory occupation is reduced by combining long and short queues; transmission coding and decoding are reduced by adopting a shared memory, and the cross-process interaction efficiency is improved; and task self-healing is realized through dual anomaly detection and process-level heartbeat monitoring.

The invention relates to a positioning module for a telescoping test of a micro motor. The positioning module comprises a carrier base, a carrier module, a needle die module, a side pushing module and a front-back moving module, an X-axis limiting part and a Y-axis limiting part are arranged at the front end and the left end of the upper end face of the carrier module correspondingly. The front-back moving module comprises an air cylinder fixed to the carrier base, a needle die sliding base in sliding connection with the carrier base, a side pushing rod and a side pushing block, wherein the side pushing rod and the side pushing block are arranged on the needle die sliding base. The needle mold module is arranged on the needle mold sliding seat, the needle mold sliding seat is driven by the air cylinder to move forwards along the Y axis, the lateral pushing rod pushes a product to be detected leftwards in the X axis in advance through the lateral pushing module to be limited by the Y-axis limiting part, and positioning of the product in the X-axis direction is achieved. The side pushing block forwards pushes the product to be tested along the Y axis to be limited by the X-axis limiting part, so that the product is positioned in the Y-axis direction; the needle die module moves forwards and is inserted into the to-be-tested product motor so that the lens of the to-be-tested product is telescopic. According to the invention, the to-be-detected camera module can be automatically positioned.

An edge device and communication method for communicating data captured at an edge device to another device. The edge device is configured to capture data of an area surrounding the edge device, to detect one or more moveable objects of one or more predetermined classes in the area from the captured data, to determine one or more location indicators indicating respective locations of said one or more objects within the area, and to communicate a message to another device at a distance of the edge device, said message including the one or more location indicators together with a time stamp indicating a time when the data was captured.