117results about "Still image data retrieval" patented technology

The invention relates to the technical field of artificial intelligence, can be applied to business scenes such as financial science and technology and medical health, and discloses an interaction intention-driven tool scheduling method, device and equipment and a medium. The method comprises the steps of obtaining to-be-processed interaction data of visual data or text data, executing cross-modal semantic analysis to generate a unified interaction intention, and sending the unified interaction intention to a server; detecting intention association strength between the matching tool and the context state data, selecting a context association mode based on the strength, determining a target dialogue node, scheduling the matching tool to perform sandbox execution to obtain a tool execution result, generating response content, and sending the response content to the server; and selectively updating the to-be-processed interaction data, the unified interaction intention, the response content, the tool execution result, the target dialogue node and the extracted service entity data to context state data. According to the method, the interaction accuracy is improved through cross-modal analysis and a switchable context association mechanism, tool decoupling is achieved in a sandbox execution mode, and the system adaptability and stability are enhanced.

A computer-implemented method, performed by a system, for creating a video representation of a file is disclosed. The method comprises receiving, by the client device a request to start a synchronization addon with a file, whose content is requested to be shared by a user of the client device, wherein synchronization of data, collaborated on in the collaboration session, is performed by a synchronization framework used by the synchronization addon, and receiving, by the recording function, a message, originating from the client device instructing the central server to capture image frames of the content displayed by an instance of the synchronization addon. The method further comprises listening, by the recording function, to event messages from the synchronization addon executing in the recording function, and determining, by the recording function, a respective event time stamp for each respective event message of the event messages to obtain metadata associated with the content.

The present invention provides a system of trademark surveillance system with image understanding for multi-country and the method thereof, which is implemented by providing a user-operated user electronic device. The user electronic device comprises a second processor and a second network interface controller. A server comprises a second application program. The second processor is connected to the server through the second network interface controller and executes the second application program to perform trademark monitoring, particularly to monitor trademark images by inputting a text description.

This application provides a training method for an image processing model, an electronic device, and a computer storage medium. The training method for the image processing model includes: obtaining a sample image group, the sample image group including a first image and a second image with the same image content; dividing the first image into regions according to image features and corresponding preset region division parameters using an image processing model to obtain at least two types of regions to be blurred; constructing blur degree data corresponding to each type of region to be blurred based on image features and corresponding blur parameters, thereby obtaining blur degree data corresponding to the first image; deblurring the second image using the image processing model based on the blur degree data corresponding to the first image to obtain a deblurred image; calculating a loss value based on the first image and the deblurred image; and adjusting the image processing model based on the loss value to deblur the image using the adjusted image processing model.

The present disclosure provides computer-implemented methods, systems, and devices for responding to requests associated with an image. A computing system obtains, wherein the image depicts a first set of textual content. The computing system determines one or more characteristics of the first set of textual content. The computing system determines a response type from a plurality of response types based on the one or more characteristics. The computing system generates a model input, wherein the model input comprises data descriptive of the first set of textual content and a prompt associated with the response type. The computing system provides providing the model input as an input to a machine-learned language model. The computing system receives a second set of text as an output of the machine-learned language model as a result of the machine-learned language model processing the model input. The computing system provides the second set of text for display to a user, wherein the second set of textual content is associated with the response type.

A computer-implemented method for managing a file is disclosed. The method comprises opening (E110) the file by means of a rendering function (610) to render at least a portion of the file as an image, and obtaining (E120) one or more event messages. For each event message of said one or more event messages, the method comprises obtaining (E130), from the rendering function (610), an image for each event message, wherein the image represents a rendered portion of the file, wherein the image is associated with a sequence indication, generating (E140) metadata based on the event message and the sequence indication, providing (E150) the metadata, and providing (E160) a video comprising a set of images, wherein the set of images comprises the image for said each event message, wherein the video is a representation of the file.

The present application relates to a kind of external parameter calibration method, device and electronic equipment, the external parameter calibration method includes: obtaining multiple frames containing texture feature plane point cloud and multiple frames containing texture feature plane image;According to multiple images, estimate three-dimensional structure point and the initial pose of camera;Plane extraction is carried out to three-dimensional structure point, and the plane pixel point in multiple images is obtained, wherein, plane pixel point is the pixel point generated by texture feature plane;According to the plane pixel point in multiple images, optimize initial pose to obtain camera pose, and obtain the first plane equation in world coordinate system;Plane extraction is carried out to point cloud, and the second plane equation is obtained;According to the first plane equation and the second plane equation and camera pose, the external parameter of laser radar camera is obtained, to obtain more accurate external parameter of laser radar camera.

The application discloses a kind of text image quality detection method, system, equipment and medium, the method includes: obtaining text image, text image is divided into training set and test set;Text image quality detection model is constructed, and training set is input into text image quality detection model for training;Test set is input into the text image quality detection model that has been trained, obtains detection result, and text image quality detection model is evaluated and optimized.The application detects the quality of text image using the text image quality detection model without reference image, does not need fixed reference image, is more suitable for practical application scene, is more flexible and practical, improves the detection precision of text image quality evaluation, and improves the accuracy and robustness of text image quality detection, realizes accurate and real-time text image quality evaluation.

A method for providing shopping information using an electronic device is disclosed. The method includes inputting a product image acquired via a camera module into an AI recognition model including an artificial neural network to obtain recognition results, and determining whether product information is recognized from the product image. When the AI recognition model fails to recognize the product information, a user input interface is displayed together with recognition failure information on a display module. User input data is received through the user input interface, and the product information is determined based on the received user input data. A query based on the product information is transmitted to a server via a communication module, and shopping information corresponding to the transmitted query is received from the server and displayed on the display module.

A server-side application is provided that transfers images associated with a medical study. The application receives a request to view a medical study and in response opens a WebSocket or a WebTransp

A computer-implemented method for managing files is disclosed. The method comprises: opening (E110) the file by a rendering function (610) to render at least a portion of the file as an image; and obtaining (E120) one or more messages. For each event message of the one or more event messages, the method comprises: acquiring (E130) an image for each event message from the rendering function (610), where the image represents a rendered portion of the file, where the image is associated with a sequence indication; generating (E140) metadata based on the event message and the sequence indication; providing (E150) the metadata; and providing (E160) a video comprising a set of images, where the set of images comprises the image for each event message, where the video is a representation of the file.

The invention relates to a method for enriching a database of medical images intended for a clinical study, comprising the steps of: - retrieving (100) a medical image to be analyzed; - identifying (103) a type of organ in the medical image to be analyzed by implementing an artificial intelligence model generated by training on a database of reference medical images whose predefined parameter values ​​are fixed; - selecting predefined parameters of the image to be analyzed according to the type of organ identified; - identifying (106) the values ​​of the predefined parameters of the medical image to be analyzed by implementing the artificial intelligence model; - storing (108) the identified parameter values ​​in metadata associated with the image to be analyzed. Figure to be published with the abstract: Fig. 1

This application discloses a wastewater discharge detection method, comprising: semantically segmenting an image to be detected to obtain a discharge area; converting the discharge area from RGB color space to HSV color space; obtaining a normalized saturation histogram and a normalized luminance histogram of the discharge area; setting a probability threshold α for saturation and performing probability statistics on the saturation histogram based on the probability threshold α; setting a probability threshold β for luminance and performing probability statistics on the luminance histogram based on the probability threshold β; and setting a wastewater assessment value μ, comparing the probability statistics results with the wastewater assessment value μ to determine whether the discharge area is discharging wastewater. This wastewater discharge detection method is based on real-time image processing, which can automatically detect whether the discharge is wastewater in a timely and effective manner, saving manpower through real-time image detection.

A device for classifying a scene in the environment of a vehicle is proposed, comprising a classification unit using a neural network to classify a scene in response to a received image representing the scene, and a learning unit to train the neural network from a set of images stored in a database (3). The device includes: - an image preprocessing module (120) to extract a set of thumbnails from a received image based on a position criterion within the image and at least one criterion relating to an image parameter, - a classification module (122) to determine, for each thumbnail, a set of membership probabilities, each associated with a class from a set of predefined classes, and - an image annotation module (124) to determine an annotation corresponding to the image from the sets of probabilities determined for all the thumbnails. Abbreviated: Figure 2

An online system performs an inference task in conjunction with the model serving system and / or interface system to generate relevant product images for query auto-completion and query suggestion to help users better navigate their search experience. The online system generates a collection of query suggestions using search query log mining. For each query suggestion in the collection of query suggestions, the online system retrieves one or more catalog images that depict the query suggestion from a product catalog. The online system constructs a prompt to a text-to-image model including the query suggestion, and a request to generate one or more query images based on the query suggestion. The online system receives the query images from the text-to-image model and ranks the catalog and query images to identify an image to display to the user in association with the query suggestion.

Systems and methods for creating, editing, sharing and distributing high-quality, media-rich web-based communications. The communications are created in a layered fashion that integrates user-selected text, colors, background patterns, images, sound, music, video, or other media. The systems and methods are used to generate, edit, broadcast, and track electronic presentations, brochures, advertisements (such as banner advertisements on highly trafficked media websites), announcements, and interactive web pages, without the need for the user to understand complex programming languages

The application relates to the technical field of visual detection, in particular to an intelligent big data supervision system and method for visual detection, which comprises a product data acquisition module, a database, a detection data analysis module, a visual detection supervision module and a product detection module, historical detection data of products subjected to visual detection are collected through the product data acquisition module, all the collected data are transmitted to the database, all the collected data are stored through the database, the historical detection data are analyzed through the detection data analysis module, a necessary degree reference value for pre-processing of product images is set, the necessary degree of pre-processing of current product images is analyzed through the visual detection supervision module, target products are selected out, and the current product is subjected to visual detection through the product detection module, so that the feature extraction speed during visual detection of the product is accelerated, and the visual detection efficiency is further improved.

To provide a determination apparatus, a determination method, and a determination program for objectively determining, rather than subjectively determining using human hands, whether or not felling has been appropriately performed based on data, to provide the results.SOLUTION: A determination apparatus 100 comprises: a plan data acquisition unit 110 for acquiring plan data indicating a felling plan for felling standing trees in a target area; a first image data acquisition unit 120 for acquiring first image data indicating a first image captured before felling in the target area; a second image data acquisition unit 130 for acquiring second image data indicating a second image captured after felling in the target area; a determination unit 150 for determining whether or not felling is appropriate based on the plan data, the first image data, and the second image data; and an output unit 160 for executing output according to the determined result.SELECTED DRAWING: Figure 1

The invention discloses a quality control method for image data of an intelligent weather phenomenon video viewer, and relates to the technical field of meteorological observation, and the method comprises the steps: obtaining a to-be-detected image; respectively carrying out format check, image availability check, image pollution check and target object missing check on the to-be-detected image; when any check is not passed, generating corresponding suspicious error information; and when all the examinations are passed, quality control information is generated. According to the method, the pixel missing image, the polluted image, the night unavailable image and the target object missing image can be effectively detected, the problem that no quality control method exists in the uploaded image data in the business is solved, the reliability of related image data information is guaranteed, and the user experience is improved. And a technical guarantee is provided for effective use of the image data of the weather phenomenon video intelligent viewer in the service.

The application relates to the field of scoliosis detection, in particular to a detection method and device for human back posture features based on images, which comprises the following steps: acquiring a back color image; inputting the back color image into a preset feature recognition network model to output coordinates of an even number of back feature points; processing the back color image to obtain a back contour image; fusing the coordinates of the back feature points into the back contour image to determine the position corresponding relationship between each back feature point and each target part in the back contour image, and determining whether target parts of the same category are isohypse by the position corresponding relationship to obtain a back posture detection result of a detected person. The technical scheme of the application is radiation-free throughout the whole process, high in efficiency, and suitable for large-scale and rapid detection of the back scoliosis of a human body.

Embodiments of the present application disclose a shadow adjustment method, device and equipment and a storage medium. The method comprises: when a shadow adjustment event is detected, obtaining a to-be-adjusted map in which a generated shadow and an irradiated object irradiated by a light source correspond to the shadow adjustment event; obtaining an outline map obtained by rendering an object outline of the irradiated object extracted from the to-be-adjusted map, and comparing the to-be-adjusted map and the outline map to obtain to-be-adjusted pixel points of the irradiated object covered by the generated shadow in the to-be-adjusted map; adjusting the to-be-adjusted pixel points, and rendering an adjusted map according to a pixel point adjustment result. The technical solution of the embodiments of the present application can present the irradiated object covered by the generated shadow.

A dynamic advertising method in which avatars corresponding to viewer-associated assets are inserted into advertising content displayed on viewer devices. Viewer records contain at least one viewer-associated avatar model which are used to selectively replace identified replaceable image elements in stored media content from content records - the system graphically renders final advertising content including the viewer-associated avatars of types corresponding to asset types assigned to at least one replaceable image element in the content. The method of tagging or preparing the mage content for use in association with the method is also disclosed.

The invention discloses a power equipment defect detection method and system, and relates to the technical field of power equipment defect detection.The method comprises the steps that multiple training power equipment sample images are obtained, standard image adaptation processing is conducted on the training power equipment sample images based on a preset defect image library, and multiple standard defect images are obtained; performing defect positioning on each training power equipment sample image according to each standard defect image to obtain a plurality of target training sample images, training a preset initial defect detection model by adopting each target training sample image to obtain a corresponding target defect detection model, and when a to-be-detected power equipment image is received, performing defect detection on the to-be-detected power equipment sample image. And inputting the to-be-detected electrical equipment image into the target defect detection model for defect detection to obtain a corresponding defect detection result. The technical problems that traditional electrical equipment defect detection mainly depends on a manual inspection method, defects are prone to missing judgment and misjudgment, and the operation reliability of the electrical equipment is reduced are solved.

Various embodiments are directed to techniques for ensuring that a negotiable instrument has not been altered between the time the instrument leaves the hands of the payor and when the check is presented for redemption by the payee by recording an image of the check in a data block in a blockchain and retrieving the image when the check is presented for redemption for comparison with the check. A match between the stored image and the check indicates that no alteration of the check has occurred.

The application provides a general keyboard anomaly detection method, comprising the following steps: a model training stage, through picture collection, correction module and data labeling processing, a classification model and a detection model are obtained; a model application stage, each key of the image keyboard is defined with a corresponding type, and a None type representing an abnormal key position type is added; a detection picture is read, and a correction module, a classification module and a detection module are sequentially operated on the detection picture, and detection information of each key is output; according to target coordinate information, category information, keyboard row inference labels and vertical coordinate offset threshold values output by a detection algorithm, the target coordinate information, the category information, the keyboard row inference labels and the vertical coordinate offset threshold values are compared with real label values of the type of product, and result data is output, the application supports self-defined multiple types of keyboards, and the compatibility is greatly improved. The detection efficiency is greatly improved, and the detection is efficiently completed. The influence of the external environment is reduced, and the stability of keyboard detection is improved.

The application provides a defogging and denoising method applied to a polarized image, and the method comprises the following steps: obtaining an original image to be defogged; obtaining a high-noise high-defogging image by using a first amplification coefficient; obtaining a low-noise low-defogging image by using a second amplification coefficient, wherein the first amplification coefficient is greater than the second amplification coefficient; obtaining a noise image according to the high-noise high-defogging image and the low-noise low-defogging image; calculating a transmission coefficient by using a first local atmospheric light intensity, and performing normalization to obtain a normalized transmission coefficient; obtaining a distance-processed noise image according to the normalized transmission coefficient and the noise image; and obtaining a low-noise high-defogging image according to the high-noise high-defogging image and the distance-processed noise image. The defogging and denoising method provided by the application can effectively remove the noise in the image without using filtering under the premise of ensuring the defogging effect, can maximize the retention of image details, and can flexibly control the degree of image defogging and denoising, thereby improving the recovery quality of the image.

This application discloses a method, apparatus, and cable clamping device for locating male ribbon cable connectors, belonging to the field of ribbon cable technology. The method includes: acquiring first point cloud information of a first male ribbon cable connector and generating a first minimum volume bounding box; segmenting the first point cloud information according to the first minimum volume bounding box to obtain second point cloud information corresponding to the male connector region of the first ribbon cable connector; generating a second minimum volume bounding box and a second coordinate system corresponding to the second minimum volume bounding box based on the second point cloud information; and cropping the second point cloud information according to the second minimum volume bounding box, the second coordinate system, a template minimum volume bounding box, and a template coordinate system to obtain third point cloud information corresponding to the male connector region of the first ribbon cable connector, generating a third minimum volume bounding box and a third coordinate system corresponding to the third minimum volume bounding box, thereby determining the first pose information of the first male ribbon cable connector. This method can improve the positioning accuracy of the male ribbon cable connector.