11results about "Still image data retrieval" patented technology

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

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.

A method and system (100) for managing video sharing in a collaboration session is disclosed. A sharing function (112) obtains a synchronization timestamp of an audio frame of the collaboration session (B122), which is used to synchronize a shared video stream with the collaboration session. The sharing function (112) determines whether the shared video stream requires more, fewer, or the same number of video frames as the video file, based on the video frame rate difference between a desired frame rate and the source frame rate of the video file. The sharing function (112) iteratively retrieves video frames from the video file stored in a storage function (140) (B140). The sharing function (112) provides the shared video stream by sending one or more generated video frames to a video communication service (110) (B160). The video communication service (110) provides the shared video stream to two client devices (121) participating in the collaboration session (B174).

The present disclosure provides a flat field correction method and device, electronic equipment and storage medium, and relates to the field of image processing, which comprises: acquiring multiple background pictures of different positions of an object to be detected; calculating first, second and third gray values of the multiple background pictures; generating a target background template image of the object to be detected according to the gray values of the multiple background pictures, the first, second and third gray values of each pixel point; and correcting an object to be detected image according to the target background template image. The method of the present disclosure does not need to guarantee the absolute blank state which is difficult to achieve when obtaining the correction template in the past, and the background template image is generated one by one according to the background pictures of the object to be detected, so that the noise reduction template is more targeted, and the quality of image noise reduction is improved.

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.

Systems and methods for generating a domain-specific conversational automated assistant. In some examples, a conversational language model is used to generate a target answer and a target action recommendation in response to each of a set of in-domain training questions. In some examples, the conversational language model is further used to generate follow-up questions to one or more of its generated target answers, and to then generate a target answer and target action recommendation to each generated follow-up question. In some examples, the processing system also generates a set of out-of-domain training examples including an out-of-domain question, a predetermined target answer, and a predetermined target action recommendation. The automated assistant may then be trained to predict the generated target answers and target action recommendations based on the associated training question or generated follow-up question, as well as any prior questions and answers in the conversation.

A method of processing satellite images comprises processing input data defining a 5 plurality of location-time-interval pairings, each comprising a location and a time interval, wherein the input dat

A method and system (100) for managing video sharing in a collaboration session is disclosed. A central server (130) obtains synchronization timestamps of audio frames associated with the collaboration session, which are used to synchronize the shared video stream with the collaboration session (B122). The central server (130) then determines whether more, fewer, or the same number of video frames are needed based on the video frame rate difference of the video files (B124). The central server (130) sets up a buffer for providing the shared video stream to the collaboration session (B130). This buffer is capable of buffering a limited number of video frames corresponding to time intervals of less than 1 second at most. The central server (130) iteratively obtains the video frames of the video file frame by frame (B140). For each video frame, the central server (130) generates (B150) zero, one, or more video frames based on the determination, and sets a timestamp for each of the generated one or more video frames. The generated one or more frames have a desired resolution, and each timestamp corresponds to a desired frame rate. Next, the central server (130) provides the shared video stream by inserting one or more generated video frames into a buffer (B160).

The application provides a three-dimensional point cloud registration method, device, system and storage medium. The point cloud registration method provided by the application removes the repeated part of the subsequent texture map and the previous texture map to obtain a de-duplicated texture map, and selects the point cloud of the de-duplicated texture map as the incomplete point cloud of the subsequent texture map according to the texture point cloud mapping relationship of the subsequent texture map in the point cloud of the subsequent texture map, so as to reduce the number of points participating in the point cloud registration calculation in the point cloud registration process, and effectively reduce the calculation amount in the point cloud registration process. Meanwhile, in the process of registering multiple point cloud data, the point cloud after each registration is mapped into the corresponding incomplete point cloud of the next subsequent texture map until all the texture maps are processed to obtain the point cloud of the measured object. Compared with the mode of mapping all the subsequent point cloud data into the first point cloud, the calculation amount is effectively reduced, and the calculation accuracy is higher.

The application discloses a target position box prediction method and device in an image, equipment and a storage medium, relates to the technical field of automatic driving, and can improve the prediction accuracy of the target position box in the image. The specific scheme comprises the following steps: obtaining a first target pixel point from a first position box of a first reference frame, wherein the first reference frame is a previous frame image at a current time; obtaining a prediction box corresponding to a target object in a current frame image according to the first target pixel point, according to the current vehicle position and the current vehicle yaw angle obtained at the current time, the first vehicle position and the first vehicle yaw angle at the first time corresponding to the first reference frame, the first target device position, the first height of the first position box and the first width of the first position box, and according to the preset calibration parameters of the acquisition device and the preset second target world position; the second target pixel point is a pixel point corresponding to the first target pixel point in a previous frame image of the first reference frame.

A computer implementation for managing files is disclosed. This method includes rendering at least a portion of a file as an image by opening the file (E110) using a rendering function (610), and obtaining one or more event messages (E120). For each of the one or more event messages, the method includes: obtaining an image corresponding to each event message from the rendering function (610) (E130), where the image represents the rendered portion of the file and is associated with a sequence instruction, generating metadata based on the event message and sequence instruction (E140), providing the metadata (E150), and providing a video containing a set of images (E160), where the set of images contains an image corresponding to each event message, and the video is a representation of the file.