Abstract: An image decoding method and apparatus and an image encoding method and apparatus are discussed. The image decoding method can include deriving an intra prediction mode of a current block, deriving reference samples including left or upper reference samples for an intra prediction on the current block, and generating a predicted block by performing the intra prediction on the current block based on the intra prediction mode and the reference samples. Based on that the intra prediction mode of the current block is a DC mode and a height of the current block is equal to a width of the current block, the intra prediction of the current block is performed by using an average value of the left reference samples adjacent to a left boundary of the current block and the upper reference samples adjacent to an upper boundary of the current block.

Abstract: An mage decoding method and apparatus and an image encoding method and apparatus are discussed. The image decoding method can include deriving an intra prediction mode of a current block, deriving reference samples being left or upper reference samples for an intra prediction on the current block, and generating a predicted block by performing the intra prediction on the current block based on the intra prediction mode and the reference samples. Based on that the intra prediction mode of the current block is a DC mode and a height of the current block is equal to a width of the current block, the intra prediction of the current block is performed by using an average value of the left reference samples adjacent to a left boundary of the current block and the upper reference samples adjacent to an upper boundary of the current block.

Abstract: An image decoding method and apparatus and an image encoding method and apparatus are discussed. The image decoding method can include deriving an intra prediction mode of a current block, deriving reference samples including left or upper reference samples for an intra prediction on the current block, and generating a predicted block by performing the intra prediction on the current block based on the intra prediction mode and the reference samples. Based on that the intra prediction mode of the current block is a DC mode and a height of the current block is equal to a width of the current block, the intra prediction of the current block is performed by using an average value of the left reference samples adjacent to a left boundary of the current block and the upper reference samples adjacent to an upper boundary of the current block.

Abstract: The present invention relates to an intra prediction method and apparatus. The image decoding method according to the present invention may comprise decoding information on intra prediction; and generating a prediction block by performing intra prediction for a current block based on the information on intra prediction. The information on intra prediction may include information on an intra prediction mode, and the intra prediction mode may include a curved intra prediction mode.

Abstract: Provided is a method and an apparatus for targeting an object in a game. The method of targeting an object in a game includes: setting a center point of a first targeting area based on a first input from a user; displaying the first targeting area surrounded by a closed curve around the center point on a screen of a user terminal; displaying a list including at least one object located in the first targeting area on the screen; and moving the first targeting area based on a second input by the user received after the first input.

Abstract: The present invention relates to an image encoding/decoding method and apparatus. An image encoding method according to the present invention may comprise generating a transform block by performing at least one of transform and quantization; grouping at least one coefficient included in the transform block into at least one coefficient group (CG); scanning at least one coefficient included in the coefficient group; and encoding the at least one coefficient.

Abstract: The present invention relates to an image encoding method and an image decoding method. The image decoding method includes partitioning a picture into a plurality of coding units, constructing a coding unit group including at least one coding unit of the plurality of coding units, obtaining coding information in units of one coding unit group, and decoding at least one coding unit of the plurality of coding units included in the coding unit group by using the obtained coding information.

Abstract: An aspect of the present invention provides a rechargeable battery which makes placement of the electrode assembly in the case during assembly easy. The rechargeable battery includes an electrode assembly including a first electrode, a separator, and a second electrode, a case housing the electrode assembly and having an opening in a plane parallel to a flat side surface of the electrode assembly, the case being electrically connected to the first electrode, a cover closing the opening in the case, and an electrode terminal mounted to a terminal opening in the case and connected to the second electrode, wherein the electrode terminal and the second electrode are insulated from the case.

Abstract: The present invention relates to an intra prediction method and apparatus. The image decoding method according to the present invention may comprise decoding information on intra prediction; and generating a prediction block by performing intra prediction for a current block based on the information on intra prediction. The information on intra prediction may include information on an intra prediction mode, and the intra prediction mode may include a curved intra prediction mode.

Abstract: The present invention relates to an intra prediction method and apparatus. The image decoding method according to the present invention may comprise decoding information on intra prediction; and generating a prediction block by performing intra prediction for a current block based on the information on intra prediction. The information on intra prediction may include information on an intra prediction mode, and the intra prediction mode may include a curved intra prediction mode.

Abstract: An image encoding/decoding method and apparatus for predicting a second color component block using a first color component block are provided. An image decoding method of the present invention comprises deriving a prediction parameter using the first color component block, and predicting the second color component block using the derived prediction parameter.

Abstract: A battery charge and discharge control device according to an embodiment of the present disclosure includes a state-of-charge (SOC) measurer measuring a SOC of a battery and a charge and discharge controller controlling a charging speed of the battery in response to the SOC of the battery being included in a preset SOC section, and the preset SOC section has change in resistance or a change in potential due to ions inserted into a material constituting the battery equal to or greater than a reference value.

Abstract: Disclosed are embodiments of a method of forming a curved glass article. In the method, a mold having a curved surface is provided. A self-adhesive layer is disposed on the curved surface. A glass sheet is bent into conformity with the curved surface at a temperature less than the glass transition temperature of the glass sheet. The glass sheet includes a first major surface and a second major surface in which the second major surface is opposite to the first major surface. The first major surface is adhered to the self-adhesive layer. A frame is bonded to the second major surface of the glass sheet, and the glass sheet is removed from the self-adhesive layer. A system for performing the method and a mold having a self-adhesive layer are also disclosed.

Abstract: An artificial intelligence (AI) system capable of simulating functions of a human brain, such as recognition and judgment, by using the machine learning algorithm such as deep learning, and an application thereof are provided. A method of learning multi-modal data according to the AI system and an application thereof includes: obtaining first context information representing a characteristic of a first signal and second context information representing a characteristic of a second signal by using a first learning network model; obtaining hidden layer information based on the first context information and the second context information by using a second learning network model; obtaining a correlation value representing a relation degree between the hidden layer information by using the second learning network model; and learning the hidden layer information in which the correlation value is derived as a maximum value.

Abstract: Disclosed are a Filipendula glaberrima alcoholic extract and solvent fractions fractionated therefrom or novel compounds 1 and 2 purely isolated from a Filipendula glaberrima ethyl acetate fraction that have an excellent inhibitory effect against HMG-CoA reductase activity, an excellent antioxidant effect and a remarkably excellent effect of suppressing the formation of foam cells in macrophages. Also, disclosed is a pharmaceutical composition or health food composition for treating, preventing and ameliorating vascular diseases, hypercholesterolemia, or heart diseases caused by hypercholesterolemia, or lowering blood cholesterol levels, containing, as active ingredients, the Filipendula glaberrima alcoholic extract and the solvent fractions or the novel compounds 1 and 2.

Abstract: A method of processing an image by a device obtaining one or more images including captured images of objects in a target space, generating metadata including information about mapping between the one or more images and a three-dimensional (3D) mesh model used to generate a virtual reality (VR) image of the target space, and transmitting the one or more images and the metadata to a terminal.

Abstract: A method of processing a substrate, with a first major surface of the substrate removably bonded to a first major surface of a first carrier and a second major surface of the substrate removably bonded to a first major surface of a second carrier, includes initiating debonding at a first location of an outer peripheral bonded interface between the substrate and the first carrier to separate a portion of the first carrier from the substrate. The method further includes propagating a first debond front from the first debonded location along a first direction extending away from the first debonded location by sequentially applying a plurality of lifting forces to the first carrier at a corresponding plurality of sequential lifting locations of the first carrier.

Abstract: The present disclosure relates to an artificial intelligence (AI) system for simulating functions of a human brain such as cognition and decision-making by using machine learning algorithms such as deep learning, and applications thereof. In particular, the present disclosure provides a method of recognizing an object by using an AI system and its application, including: extracting pieces of first feature information respectively regarding a plurality of images, each image including an object; generating at least one piece of second feature information representing a correlation between the plurality of images by combining together the extracted pieces of first feature information respectively regarding the plurality of images; and recognizing, based on the at least one piece of second feature information, the object included in each of the plurality of images by using a pre-generated learning network model.

Abstract: According to the present disclosure, an artificial intelligence (AI) system and a method of providing content according to an application of the AI system are provided. The method includes: obtaining one or more images included in the content; generating additional content for guiding user information, the additional content corresponding to the one or more images, based on feature information extracted from the one or more images; when receiving a request for reproducing the content, synchronizing the generated additional content with the one or more images; and reproducing the content and the additional content, according to a result of the synchronizing.

Abstract: Provided are an artificial intelligence (AI) system that simulates functions of a human brain such as recognition and judgment by utilizing a machine learning algorithm such as deep learning, etc., and an application of the AI system. Provided are an AI system and a method of recognizing an object according to the application of the AI system, the method including: obtaining a plurality of pieces of sensor data about the object from a plurality of different types of sensors; converting at least some of the plurality of pieces of sensor data into two-dimensional (2D) sensor data; and recognizing the object by using a previously generated learning network model based on 2D image data obtained from an image sensor, which is one of the plurality of sensors, and the 2D sensor data.