Abstract:
An electronic device is provided. The electronic device includes a housing that includes a first face, a second face that is directed opposite to the first face, and a side face that at least partially enclose a space between the first face and the second face, a first metallic member, a second metallic member, and a third metallic member that form a side face, a sensor configured to detect whether an external object comes in contact with at least one of the first metallic member, the second metallic member, and the third metallic member, and to generate a signal, and a circuit configured to change an electric path between at least one of the first metallic member, the second metallic member, and the third metallic member, and the ground member, at least partially based on the generated signal.
Abstract:
A system and method that can customize mobile advertising services and increase the effectiveness of advertising is provided. The method includes registering contact details of one or more advertisers in a phone book, receiving one or more mobile advertising messages from the registered advertisers, notifying a user of the reception of the mobile advertising messages, and displaying the received mobile advertising messages according to the user's confirmation request.
Abstract:
Provided is a method of adaptively performing artificial intelligence (AI) downscaling on an image during a video telephone call of a user terminal. The method includes obtaining, from an opposite user terminal, AI upscaling support information of the opposite user terminal that is a target of a video telephone call, determining whether the user terminal is to perform AI downscaling on an original image, based on the AI upscaling support information, based on determining that the user terminal is to perform AI downscaling on the original image, obtaining a first image by AI downscaling the original image using a downscaling deep neural network (DNN), generating image data by performing first encoding on the first image, and transmitting AI data including information related to the AI downscaling and the image data.
Abstract:
A portable terminal having a bended display divided into a main region of a front surface and a sub-region of a side of the portable terminal and operating functions of the portable terminal in connection with the main region and the sub-region, and a method of operating the same are provided. The method of operating functions of a portable terminal having a bended display, includes receiving an input of an event, determining a type of the input event, outputting event information, according to an internal event input based on the bended display, through at least one of a main region and a sub-region of the bended display when the input event is the internal event, and outputting event information, according to an external event input from an outside source, through the sub-region of the bended display when the input event is the external event.
Abstract:
A portable terminal having a bended display divided into a main region of a front surface and a sub-region of a side of the portable terminal and operating functions of the portable terminal in connection with the main region and the sub-region, and a method of operating the same are provided. The method of operating functions of a portable terminal having a bended display, includes receiving an input of an event, determining a type of the input event, outputting event information, according to an internal event input based on the bended display, through at least one of a main region and a sub-region of the bended display when the input event is the internal event, and outputting event information, according to an external event input from an outside source, through the sub-region of the bended display when the input event is the external event.
Abstract:
Provided is a method of adaptively performing artificial intelligence (AI) downscaling on an image during a video telephone call of a user terminal. The method includes obtaining, from an opposite user terminal, AI upscaling support information of the opposite user terminal that is a target of a video telephone call, determining whether the user terminal is to perform AI downscaling on an original image, based on the AI upscaling support information, based on determining that the user terminal is to perform AI downscaling on the original image, obtaining a first image by AI downscaling the original image using a downscaling deep neural network (DNN), generating image data by performing first encoding on the first image, and transmitting AI data including information related to the AI downscaling and the image data.
Abstract:
An AI decoding apparatus includes a memory storing instructions and a processor configured to execute the instructions to obtain AI data related to AI down-scaling of an original image and image data generated as a result of encoding a first image, obtain a second image corresponding to the first image by decoding the image data, determine a resolution ratio in a horizontal direction and a resolution ratio in a vertical direction between the original image and the first image, based on the AI data, and obtain, by an up-scaling deep neural network (DNN), a third image in which a resolution in at least one of a horizontal direction and a vertical direction is increased from the second image based on the resolution ratio in the horizontal direction and the resolution ratio in the vertical direction.
Abstract:
An artificial intelligence (AI) decoding apparatus includes at least one processor configured to execute one or more instructions to: obtain a second image corresponding to a first image by performing first decoding on image data included in a main bitstream, obtain AI upscaling activation flag information included in AI data of a sub-bitstream, determine whether to perform AI upscaling on the second image, based on the AI upscaling activation flag information, when it is determined that AI upscaling is to be performed on the second image, obtain a third image by performing AI upscaling on the second image, through an upscaling deep neural network (DNN) set according to upscaling DNN information, the upscaling DNN information selected from among a plurality of pieces of pre-stored upscaling DNN information based on at least a portion of the image data and/or at least a portion of AI sub-data.
Abstract:
Provided is an artificial intelligence (AI) decoding apparatus includes: a memory storing one or more instructions; and a processor configured to execute the one or more instructions stored in the memory, the processor is configured to: obtain AI data related to AI down-scaling an original image to a first image; obtain image data corresponding to an encoding result on the first image; obtain a second image corresponding to the first image by performing a decoding on the image data; obtain deep neural network (DNN) setting information among a plurality of DNN setting information from the AI data; and obtain, by an up-scaling DNN, a third image by performing the AI up-scaling on the second image, the up-scaling DNN being configured with the obtained DNN setting information, wherein the plurality of DNN setting information comprises a parameter used in the up-scaling DNN, the parameter being obtained through joint training of the up-scaling DNN and a down-scaling DNN, and wherein the down-scaling DNN is used to obtain the first image from the original image.
Abstract:
An artificial intelligence (AI) decoding apparatus includes a memory storing one or more instructions, and a processor configured to execute the stored one or more instructions, to obtain image data corresponding to a first image that is encoded, obtain a second image corresponding to the first image by decoding the obtained image data, determine whether to perform AI up-scaling of the obtained second image, based on the AI up-scaling of the obtained second image being determined to be performed, obtain a third image by performing the AI up-scaling of the obtained second image through an up-scaling deep neural network (DNN), and output the obtained third image, and based on the AI up-scaling of the obtained second image being determined to be not performed, output the obtained second image.