42 results about "Screen capture" patented technology

Autonomous generation includes generating, with a large language model (LLM), an action list for performing an extraction task from at least one website. Generating the action list may include for each action in the action list performing operations. The operations include capturing current webpage data including a screenshot of a current webpage and a set of interactable widgets, obtaining, using an LLM processing the current webpage data, a next action attribute set, adding the next action attribute set, and performing the next action. Autonomous generation also includes traversing the action list to filter out at least one superfluous action, generating, after filtering, a set of machine executable instructions from the action list, and storing the set of machine executable instructions associated with a task identifier. Autonomous generation also includes executing the set of machine executable instructions to extract a data element from the at least one website.

Generation and use of screenshots of interactive displays are provided. A screenshot is received. The screenshot comprises an area of an interactive display. An interactive object is identified within the area of the interactive display. The interactive object corresponds to a function. A simulated interactive object corresponding to the interactive object is generated. The simulated interactive object corresponds to the function. A composite screenshot comprising the screenshot and the simulated interactive object is rendered for display, on a display.

The present application discloses a remote control method, apparatus, device, and medium. The method applicable to a controlled device includes: creating a first screen capture task based on a GDI mode and a second screen capture task based on a DirectX mode; calling, in a target screen capture frequency, the first screen capture task and the second screen capture task to simultaneously perform screen capture; determining whether a first image is same as a second image, where the second image is an image of a previous frame of the first image obtained by calling the second screen capture task to perform screen capture; performing, if the first image is different from the second image, target processing on an image obtained by calling the first screen capture task to perform screen capture; and reducing, if the first image is the same as the second image, the target screen capture frequency.

A technique is described for improved issue reporting by a receiving device such as a set-top boxes for satellite and cable television services. In an example embodiment, the receiving device generates an issue report based on internal operational logs, captured screens and / or video of a visual output, and a recording of the user's voice that includes a description of the issue they are experiencing. This issue report can be generated as an object file that can then be transmitted, via a communications network, to an issue reporting platform for processing, for example, by a technical support representative or an automated troubleshooting system.

An arrangement for automated testing of mobile devices comprising a learning arrangement for learning how to use test devices that do not match with an earlier already defined test case pattern. In the arrangement the learning arrangement generates instructions for performing a set of tasks. The tasks are then executed in the mobile device being tested. The mobile device provides feedback in form of error / success messages, screenshots, source code, return values and similar. Based on the feedback and earlier accumulated information the learning entity can generate a new set of instructions in order to execute the set of tasks successfully.

A screenshot processing method, relating to the technical field of image processing. The method includes: performing contour recognition on the current picture so as to determine, according to the obtained contour recognition result, a candidate capturing area (S210); in response to an instruction of a screenshot operation, determining at least one target capturing area in the current picture according to the instruction of the screenshot operation and the candidate capturing area (S220); and performing the screenshot operation on the current picture on the basis of the at least one target capturing area so as to generate a target image (S230).

A crawler vehicle has a chassis (2); a driver' s cabin (3) mounted on the chassis (2); an acquisition unit (4) configured to acquire operational data indicative of an environment surrounding the crawler vehicle (1); a screen (5, 25, 34, 35), which is arranged in the driver ' s cabin (3) and is configured to display a screenshot; and a control unit (6), which is in communication with the acquisition unit (4) and with the screen (5, 25, 34, 35) and is configured to process the operational data acquired by the acquisition unit (4) so as to superimpose visual indicators (36, 37, 38, 39, 40, 41) on a reproduction of the environment surrounding the crawler vehicle (1) and to control the screenshot displayed by the screen (5, 25, 34, 35) so as to display said visual indicators (36, 37, 38, 39, 40, 41) superimposed on the reproduction of the environment surrounding the crawler vehicle (1).

This application discloses a method, apparatus, device, and storage medium for detecting off-color bright lines on a display panel based on CCD sensing, relating to the field of display panel detection technology. The method includes: acquiring an off-color image of the display panel under a preset color screen captured by the CCD imaging device; preprocessing the off-color image to obtain morphological feature images of different channels; performing line detection on each of the morphological feature images to obtain line feature information of different channels; and merging the line feature information of different channels to obtain a detection result. By employing multi-channel separation, morphological feature enhancement, and fusion detection techniques, this method solves the problems of uncertainty and weak contrast in existing detection methods when off-color bright lines appear under different color backgrounds, making stable identification difficult. Compared with existing technologies, it achieves high-sensitivity detection and precise positioning of off-color bright lines under different background colors, improving the accuracy and adaptability of the detection.

Media, methods, and systems are provided for screen sharing. A user may initiate a video recording. A recording preview interface may be displayed for the user to preview the video recording before beginning the recording. The recording preview interface may comprise a live video preview of the user and of a window or application being shared. When the user selects a window or application for previewing that may cause an infinity mirror effect to occur, a screenshot of the window or application may be generated. The screenshot may be rendered over the live video preview of the window or application to obscure the infinity mirror effect. When the user initiates recording, the screenshot may be removed to expose the live video. The screenshot may be cached and retrieved if the user navigates away and then returns to the preview of the window or application causing the infinity mirror effect.

This disclosure provides a method for transmitting privacy information, as well as a terminal device, computer device, and storage medium. The method includes: sending a screen image and user-submitted natural language commands to an AI large-scale model, enabling the AI ​​large-scale model to analyze the screen image and user-submitted natural language commands, and outputting operation commands based on the analysis results; simulating user operation of the screen image according to the operation commands to control a corresponding target application; acquiring a screenshot of the screen after controlling the target application, and determining whether the target application is a privacy application; if the target application is a privacy application, using a pre-trained AI small model to identify privacy information in the screenshot; blurring the privacy information in the screenshot, and sending the blurred screen image to the AI ​​large-scale model. This privacy information transmission method can ensure the security of privacy information in the screen image data transmitted by the terminal device to the AI ​​large-scale model.

An electronic device may include a display, a processor, and a memory. The processor may instruct the electronic device to: display a first execution screen of a first application; display a second execution screen of a voice assistant application, second execution screen overlaid on a partial area of the first execution screen of the first application; receive a screen capture command through the voice assistant application while the second execution screen is displayed overlaid on the partial area of the first execution screen; and perform screen capture based on the screen capture command while the second execution screen is displayed overlaid on the partial area of the first execution screen, the screen capture being performed by saving an image of the first execution screen, on which an image of the second execution screen is not overlaid, in a partial area of the first execution screen.

This invention discloses a multi-application message monitoring method and system based on audio features, belonging to the field of computer application technology. The method includes: acquiring process information of target applications; creating independent audio capture streams for each target application based on content filtering functionality using screen capture technology to achieve application-level audio isolation; acquiring audio data in real time through the audio capture streams and calculating volume; using a state machine to identify short-duration prompt tone features in the audio data according to preset volume thresholds and duration ranges; filtering repetitive sound events for each target application within a preset time window; and generating and outputting message events when a sound event matching the features is identified. This invention combines application-level audio isolation with state machine recognition to achieve non-intrusive, highly accurate unified monitoring of multi-application messages, effectively solving the problems of strong dependence and high intrusion in existing technologies, and is suitable for multi-platform message management scenarios such as e-commerce customer service.

This invention discloses a non-intrusive AI-based automated monitoring system for new energy production, relating to the fields of industrial automation and intelligent monitoring technology. It includes a screen capture module, an action execution module, a multimodal information extraction module, a state fusion and confidence assessment module, an SC3 closed-loop monitoring control module, a process orchestration module, and a log auditing module. In each monitoring cycle, the system locks an interface snapshot and generates a set of interface anchor points and a set of readings. Through view positioning and region constraints, it performs structured extraction of readings to form a state candidate set. Combining recognition confidence, cross-frame stability, and cross-view consistency, it calculates state confidence and generates a state vector, constructs a conflict set, and performs gating decisions. Based on the afterimage verification results, it performs rollback or locking processing. The log auditing module records the entire process as a chain of evidence, achieving reliable closed-loop control of the monitoring process.

Embodiments of the disclosure provide a method, apparatus, device, computer-readable storage medium and product for displaying code. The method includes: displaying, in a preset first display area, a screenshot interface of current display content of a target application software to be analyzed, and displaying at least one triggerable control in the screenshot interface; and in response to a triggering on a target triggerable control, displaying, in a preset second display area, code information corresponding to the triggered target triggerable control.

Arrangements for detecting and resolving anomalies are provided. A computing platform may train an artificial intelligence (AI) engine. The computing platform may configure one or more anomaly detection rules and deploy the one or more anomaly detection rules. The computing platform may receive an encrypted screenshot. The computing platform may decrypt the encrypted screenshot. The computing platform may input the decrypted screenshot into the AI engine. The computing platform may output, based on analyzing the decrypted screenshot using the AI engine, an action to resolve an identified anomaly. The computing platform may execute the action to resolve the identified anomaly.

Computer-implemented methods and systems for validating outcomes in livestreamed video events are provided. The methods involve receiving a live video stream, generating a broadcast feed and a parallel analysis feed, selecting video frames at a cadence, and adding timestamps and checksums to the selected frames. An artificial intelligence (AI) vision model detects irregularities in the video frames, and an AI optical character recognition (OCR) or vision-LLM model determines an outcome state, such as victory, defeat, or mission completion. An outcome record is generated, including the outcome state, timestamp, confidence score, and references to video frames, and sent to a web server for display. The system includes modules for screen capture, video / audio recording, metadata collection, and AI analysis to detect irregularities and generate reports. The methods and systems are able to validate outcomes in livestreamed events and settle prediction markets.

A method, according to one approach, is for: receiving a screenshot of a graphical user interface on a base device output in response to the base device accessing a web page. The screenshot is used to identify elements in the graphical user interface. Moreover, outer borders of the respective identified elements are marked. An original distribution of the identified elements is determined, and an original area inside the outer borders is also determined. The method further includes determining original margin sizes between edges of the graphical user interface and the outer border of adjacent ones of the identified elements.

The embodiment of the application is suitable for the field of communication technology, and provides a method for preventing screen capture, a terminal device and a storage medium. A first terminal device and a second terminal device perform a screen sharing service, and the method for preventing screen capture comprises the following steps: the first terminal device generates a first notification message and sends the first notification message to the second terminal device. The first notification message comprises first indication information for indicating that the second terminal device is prohibited from capturing a screen. The second terminal device sets screen capture attribute information of a display window of the screen sharing service according to the first indication information. The second terminal device sends a first response message to the first terminal device. The first terminal device displays a first control in the display window of the screen sharing service, and the display state of the first control indicates that the second terminal device is prohibited from capturing a screen. The method for preventing screen capture provided by the embodiment of the application has a simple message flow and a small number of messages, and realizes the prevention of screen capture of a peer terminal device.

A digital adoption platform includes a page change identification technique. The page change identification technique is platform and application agnostic. Changes in screenshots of a UI of an application are compared. Differences between screenshots are compared using a cross-correlation technique. Trigger conditions are defined to reduce the computational resources required. Additional optimizations to reduce processing resources and optimize accuracy may also be included.

This invention discloses a method for separating and identifying the authenticity of AI-generated content in distorted images, belonging to the fields of image forensics, AI-generated content detection, computer vision, and image credibility verification. This method addresses the problem that original metadata, content credentials, and generation parameters are easily lost or invalidated after images are transferred through platforms, screenshots, screen captures, or printed images. First, the method acquires the image to be detected and reads the image data, extracting propagation state features such as resolution ratio, compression marks, boundary regions, moiré patterns, paper texture, noise residuals, and file structure. Then, based on these propagation state features, the propagation state of the image to be detected is identified, and the corresponding detection branch is invoked to determine the effective content area, extracting content authenticity features and acquisition authenticity features respectively. Next, weights are assigned to various features according to the propagation state and dynamically fused to calculate the content authenticity risk result and acquisition authenticity judgment result. Finally, an authenticity separation result is generated, outputting a detection report containing the propagation state, acquisition authenticity, content authenticity, AI generation risk level, evidence items, and uncertainty explanation. This invention can distinguish between the authenticity of the image acquisition method and whether the content carried by the image has the risk of AI generation, even when the original image file information is invalid. It is applicable to the auxiliary identification of AI-generated content in scenarios such as screenshots, platform transfers, screen re-photographs, printed re-photographs, and mixed transmission distortion.

A server monitors a sequence of screen captures from a radiotherapy treatment planning platform's user interface, operated by medical professionals. The server generates a training dataset comprising a time series of the screen captures and trains a machine learning model using this dataset. The trained model is configured to predict visual attributes of the user interface, determining the next screen's attributes based on prior interactions. When executed, the model predicts future visual attributes of the interface as a user interacts with the current screen, offering real-time guidance for navigating the treatment planning platform.

The application discloses a system for saving last screen information of a host, which comprises a watchdog triggering module, a screen capturing module, a temporary storage module, a screen information request module and a screen information processing module. The watchdog triggering module is used to send a screen capturing triggering signal to control the screen capturing module to perform a screen capturing operation. The screen capturing module is used to perform a screen capturing operation according to the received screen capturing triggering signal. The temporary storage module is used to store the screen information obtained by the screen capturing module. The screen information request module is used to receive screen information request information, verify the legality of the screen information request information, read corresponding screen information in the temporary storage module according to the requirements of the screen information request information, and send the screen information to the screen information processing module. The screen information processing module is used to process the received screen information and send the screen information to a remote monitoring host. The application can improve the defects of the prior art and improve the accuracy of screen information extraction.

Systems and methods for interacting with smart documents are disclosed. The system includes a document user interface that receives access requests, communicates with the smart document, and displays the content of the document. Features include rendering layouts tailored to user roles and devices, authentication mechanisms, and security measures such as screenshot prevention and client-side encryption, among a variety of others. The interface may support multi-panel displays, dynamic configurations, and other functionality like scheduling reports, marketing actions, and due diligence processes. Various other methods, systems, and features are also disclosed.

A digital adoption platform includes a page change identification technique. The page change identification technique is platform and application agnostic. Changes in screenshots of a UI of an application are compared. Differences between screenshots are compared using a cross-correlation technique. Trigger conditions are defined to reduce the computational resources required. Additional optimizations to reduce processing resources and optimize accuracy may also be included.

A technique for integrating applications through web interface automation uses natural language instructions and multimodal AI to interact with target applications without requiring APIs. An application handler receives requests from client applications and provides configuration data including a website address, natural language task instructions, and completion criteria. A web task orchestration service processes screenshots through a perception agent that marks interactive elements, while a multimodal language model analyzes the marked screenshots and determines appropriate actions. A browser agent executes the actions on the web interface until completion criteria are met. The technique enables seamless integration between applications by leveraging existing web interfaces rather than requiring dedicated API development.

The embodiment of the present disclosure provides a cloud mobile phone-based remote real-time streaming screenshot method, and belongs to the technical field of data processing. Specifically, a memory file device logically bound to a cloud mobile phone instance is created on a host computer, and a virtual file device driver module is configured inside the cloud mobile phone instance. When a proxy program on the host computer receives a screen data request from a remote client, a read operation is performed on the memory file device. When the read operation is intercepted by the virtual file device driver module, the virtual file device driver module controls a screenshot module inside the cloud mobile phone instance to capture original pixel data of a current frame screen. The virtual file device driver module directly writes the original pixel data in the form of a byte stream into a buffer of the memory file device. The proxy program reads the byte stream from the memory file device in a streaming manner, encodes the byte stream, and then transmits the byte stream to the remote client through a network. Through the scheme of the present disclosure, the screenshot efficiency and real-time performance are improved.

This invention discloses a cloud-based collaborative intelligent UAV detection and capture system, comprising: a capture UAV configuration and data acquisition module, which acquires environmental images and attitude navigation data of the target area and uploads them to a cloud-based collaborative platform; an improved RepPoints point set detection module, which outputs candidate target 2D point sets; a 3D point set reconstruction module, which generates an initial 3D point set based on the 2D point set and attitude navigation data; a topology constraint correction module, which obtains a topologically consistent 3D point set; a capture prototype sparse coding module, which generates candidate capture 3D point sets; a capture feasible region screening module, which screens capture feasible 3D point sets based on dynamic constraints; and a spatial risk and capture trajectory planning module, which constructs a spatial risk field and outputs capture trajectory control commands. This invention achieves integrated multi-UAV collaborative point set reconstruction and trajectory planning, improving target capture stability.