Abstract:
A domain adaptation-based object recognition apparatus includes a memory configured to store a domain adaptation-based object recognition program and a processor configured to execute the program. The processor learns a generative model for generating a feature or an image similar to a gallery image on the basis of domain adaptation in association with an input probe image and learns an object recognition classification model by using a learning database corresponding to the gallery image and the input probe image, thereby performing object recognition using the input probe image.
Abstract:
Disclosed are an apparatus for collecting lifelog data and a method thereof according to the present invention.The present invention relates to an apparatus for collecting lifelog data and a method thereof, which collect information for analyzing a behavior pattern from devices used by a user in everyday life, convert the collected information according to a preset schema, and provide the converted information.
Abstract:
A method of a base station may comprise: determining one of machine learning (ML) models for receiving channel information for a channel to communicate with a terminal based on capability information of the terminal; providing configuration information of the determined ML model to the terminal; updating the determined ML model through online training with the terminal; and receiving channel information using the updated ML model from the terminal when communicating with the terminal.
Abstract:
Provided is a method and apparatus for selecting a beamformee station (STA) in a multi-user multiple-input and multiple-output (MU-MIMO) communication system, the method including acquiring channel information associated with a beamformee STA among a plurality of beamformee STAs, verifying whether acquiring channel information associated with a subsequent beamformee STA of the beamformee STA is advantageous or disadvantageous, and determining, based on a result of the verifying, whether the channel information associated with the subsequent beamformee STA is acquired.
Abstract:
A method of identifying AI/ML functionalities/models supported for mobile communication operated in mobile communication systems including a base station and one or more terminals may comprise: identifying, by at least one of the base station or the one or more terminals, information related to the AI/ML functionalities supportable by the one or more terminals; and identifying, by at least one of the base station or the one or more terminals, AI/ML model information supportable by the one or more terminals.
Abstract:
An electronic device according to an embodiment disclosed herein may include a memory including at least one instruction and a processor. By executing the at least one instruction, the processor may check feature information corresponding to a video and including at least one of an appearance-related feature value and a motion-related feature value from the video, calculate at least one of a starting score related to a starting point of an action instance, an ending score related to an ending point of an action instance, and a relatedness score between action instances on the basis of the feature information corresponding to the video, the action instances being included in the video, and generate an action proposal included in the video on the basis of the at least one score.
Abstract:
Provided is a method and apparatus for selecting a beamformee station (STA) in a multi-user multiple-input and multiple-output (MU-MIMO) communication system, the method including acquiring channel information associated with a beamformee STA among a plurality of beamformee STAs, verifying whether acquiring channel information associated with a subsequent beamformee STA of the beamformee STA is advantageous or disadvantageous, and determining, based on a result of the verifying, whether the channel information associated with the subsequent beamformee STA is acquired.
Abstract:
An operation method performed by a mobile base station in a communication system may comprise: obtaining altitude information; configuring altitude indicator information indicating whether the obtained altitude information is higher or lower than an altitude reference in cooperation with a drone management device based on the obtained altitude information; and transmitting the configured altitude indicator information to a terminal.
Abstract:
Provided is a dynamic object detecting technique, and more specifically, a system and method for determining a state of a motion of a camera on the basis of a local motion estimated on the basis of a video captured by a dynamic camera and a result of analyzing a global motion, flexibly updating a background model according to the state of the motion of the camera, and flexibly detecting a dynamic object according to the state of the motion of the camera.