Abstract: In an embodiment an apparatus includes a processor configured to generate a feature extraction module using a dataset in which an attribute for each object is defined, receive an image obtained by a camera, extract an attribute of an object of interest from the image using the learned feature extraction module, identify an object re-identification candidate group based on the extracted attribute of the object of interest and re-identify the object of interest based on the identified object re-identification candidate group.

Abstract: An apparatus and a method for re-identifying an object to improve object re-identification performance using attribute information of the object are provided. The apparatus trains an object representation extraction model to train attribute representations, inputs an image obtained by a camera to the trained object representation extraction model, extracts object representations from the image using the trained object representation extraction model, and performs object re-identification based on the object representations.

Abstract: An embodiment user awareness device includes a processor configured to receive first information about a first user from a first device, specify the first user based on a result of comparing the first information with pre-registration information, transmit data corresponding to a first service to the first device to provide the first user with the first service based on the pre-registration information, receive data on a history of the first service from the first device, receive second information about a second user from a second device, compare the first information with the second information to determine whether the second user is the first user, and transmit data corresponding to a second service associated with the first service to the second device to provide the second user with the second service in response to the second user being the first user.

Abstract: An embodiment device includes a memory configured to store a lookup table in which target speeds corresponding to genders and ages are recorded and a controller configured to detect a face from an image photographed by a camera provided in a robot, estimate a gender and an age corresponding to the face based on a deep learning model, search the lookup table for a target speed corresponding to the estimated gender and the estimated age, and determine the target speed as a movement speed of the robot.

Abstract: The present disclosure relates to a facility guide robot that provides necessary information to a user who uses the facility while moving inside the facility. Specifically, the present disclosure relates to a facility guide robot and a facility guide method using the same, wherein the facility guide robot may actively provide the guide information to the facility users before the facility user requests to use the facility guide robot. That is, the convenience of the facility user may be improved by allowing the facility guide robot to provide the guide information necessary to the facility user before the facility user, who needs the guide, checks or calls the facility guide robot to receive the guide information.

Abstract: Disclosed are a method and an apparatus for recommending clothing coordination information in the 5G communication environment by executing an artificial intelligence (AI) algorithm and/or a machine learning algorithm, which have been mounted therein.

Abstract: Disclosed are a water purifier and a control method thereof for controlling a main body by executing an artificial intelligence (AI) algorithm or a machine learning algorithm in a 5G environment established for the Internet of things. The control method of the water purifier according to the present disclosure includes a photographing step, a scanning step, a recognizing step, a calculating step, a determining step, and a water discharging step. When the water discharging step is initiated, the distance sensor generates real-time height information on the water surface, and may stop discharging water before a real-time height exceeds the highest point height.

Abstract: Provided are a method for determining a representative image of a video with reference to a representative object, and an electronic apparatus for processing the method. A method for determining a representative image of a video may comprise acquiring a video, determining a representative object of the video from at least one object appearing in the video, and determining a representative image of the video on the basis of an image score representing visual importance of the representative object. Accordingly, an image in which a representative object is the most visually conspicuous may be determined as a representative image of a video.

Abstract: The present disclosure relates to a facility guide robot that provides necessary information to a user who uses the facility while moving inside the facility. Specifically, the present disclosure relates to a facility guide robot and a facility guide method using the same, wherein the facility guide robot may actively provide the guide information to the facility users before the facility user requests to use the facility guide robot. That is, the convenience of the facility user may be improved by allowing the facility guide robot to provide the guide information necessary to the facility user before the facility user, who needs the guide, checks or calls the facility guide robot to receive the guide information.

Abstract: Disclosed is a trained model generating method and apparatus that assesses an acquisition price of a subscription product by executing an artificial intelligence (AI) algorithm or a machine learning algorithm in a 5G environment connected for the Internet of Things, and that reinforces a trained model by reflecting, as a reward, a result of suggesting to a user to acquire the product. A product price assessing method according to one embodiment of the present disclosure may include: applying at least one of user information, product information, or environment information, or preprocessed data thereof to a machine learning-based first trained model; and assessing a product price of a product related to the product information based on the first trained model. Reinforcement learning may be conducted to the first trained model by reflecting, as a reward, whether the user determines to acquire the product at the assessed product price.

Abstract: Disclosed are a method and an apparatus for recommending clothing coordination information in the 5G communication environment by executing an artificial intelligence (AI) algorithm and/or a machine learning algorithm, which have been mounted therein.

Abstract: Disclosed are a water purifier and a control method thereof for controlling a main body by executing an artificial intelligence (AI) algorithm or a machine learning algorithm in a 5G environment established for the Internet of things. The control method of the water purifier according to the present disclosure includes a photographing step, a scanning step, a recognizing step, a calculating step, a determining step, and a water discharging step. When the water discharging step is initiated, the distance sensor generates real-time height information on the water surface, and may stop discharging water before a real-time height exceeds the highest point height.