Abstract:
At least one example embodiment discloses a user authentication method including acquiring representative reference images classified from a pre-stored first reference image of a user based on desired criteria, acquiring representative input images classified from a first input image based on the desired criteria, calculating a similarity between the first input image and the first reference image based on the representative input images and the representative reference images, and authenticating a user based on the calculated similarity.
Abstract:
A radio unit (RU) is provided. The RU includes memory storing instructions, one or more transceivers configured to transmit signals or receive signals on a fronthaul interface, and one or more processors. Wherein the instructions cause, when executed by the one or more processors, the RU to receive, from a distributed unit (DU), a control plane (C-plane) message including section information for user equipment (UE) scheduling information and section extension information for a group configuration of multiple ports, wherein the section information including information on a resource region of a section description and a UE identifier, and the section extension information including information on a beam group type, information on the number of one or more ports indicated by the section extension information, and a UE identifier per port, and, in case that a UE identifier of a specified port is set to 0x7FFF in the C-plane message, identify that the resource region is not allocated for the specified port.
Abstract:
The present disclosure relates to a communication technique for converging IoT technology with a 5G communication system for supporting a higher data transmission rate beyond a 4G system, and a system therefor. The present disclosure may be applied to an intelligent service (for example, a smart home, a smart building, a smart city, a smart car or connected car, health care, digital education, retail business, a security and safety-related service, etc.) on the basis of 5G communication technology and IoT-related technology. A communication method of a terminal of a mobile communication system, according to one embodiment of the present specification, comprises the steps of: acquiring moving speed information of a terminal; determining a reception beam candidate group on the basis of the moving speed information; and determining a reception beam, in the reception beam candidate group, for receiving a signal.
Abstract:
The present disclosure relates to a pre-5th-Generation (5G) or 5G communication system to be provided for supporting higher data rates beyond 4th-Generation (4G) communication system such as Long Term Evolution (LTE). According to an embodiment of the disclosure, in a wireless communication system, a remote terminal transmits a relay request message to a target relay terminal. The remote terminal performs an IP allocation procedure with the target relay terminal. The remote terminal performs relay communication with the target relay terminal on the basis of the IP allocation procedure. The IP allocation procedure is performed using an IP address which has been used in previous relay communication with a source relay terminal.
Abstract:
Disclosed is a face detection method and apparatus, the method including detecting a candidate area from a target image using a first sliding window moving at an interval of a first step length and detecting a face area in the candidate area using a second sliding window moving at an interval of a second step length less than the first step length.
Abstract:
A method and an apparatus for recognizing an object are disclosed. The apparatus may extract a plurality of features from an input image using a single recognition model and recognize an object in the input image based on the extracted features. The single recognition model may include at least one compression layer configured to compress input information and at least one decompression layer configured to decompress the compressed information to determine the features.
Abstract:
A user recognition method and apparatus, the user recognition method including performing a liveness test by extracting a first feature of a first image acquired by capturing a user, and recognizing the user by extracting a second feature of the first image based on a result of the liveness test, is provided.
Abstract:
A pre-5th-Generation (5G) or 5G communication system for supporting higher data rates Beyond 4th-Generation (4G) communication system such as Long Term Evolution (LTE) is provided. The device of a radio unit (RU) of a base station in a wireless communication system includes at least one transceiver and at least one processor coupled to the at least one transceiver, wherein the at least one processor is configured to receive a first control message including a section extension field from a digital unit (DU) via a fronthaul interface, identify additional information based on the section extension field, and acquire a beamforming weight based on the additional information, wherein the first control message is configured to schedule a terminal in a control plane.
Abstract:
A pre-5th-Generation (5G) or 5G communication system for supporting higher data rates Beyond 4th-Generation (4G) communication system such as Long Term Evolution (LTE) is provided. The device of a radio unit (RU) of a base station in a wireless communication system includes at least one transceiver and at least one processor coupled to the at least one transceiver, wherein the at least one processor is configured to receive a first control message including a section extension field from a digital unit (DU) via a fronthaul interface, identify additional information based on the section extension field, and acquire a beamforming weight based on the additional information, wherein the first control message is configured to schedule a terminal in a control plane.
Abstract:
An electronic device is disclosed. The electronic device may comprise: a memory in which information on a first artificial intelligence model learned through first learning data and information on a second artificial intelligence model learned through the first learning data are stored; and a processor connected to the memory to control the electronic device, wherein the processor is configured to: input second learning data to each of the first artificial intelligence model and the second artificial intelligence model and relearns the second artificial intelligence model on the basis of an output of each of a plurality of first layers included in the first artificial intelligence model and an output of each of a plurality of second layers included in the second artificial intelligence model, each of the plurality of first layers includes a plurality of two-dimensional filters, and each of the plurality of second layers includes a plurality of filters obtained by reducing the size of each of the plurality of two-dimensional filters of a corresponding first layer.