Abstract: Provided is a method of decoding a video according to an embodiment, the method including determining at least one processing block for splitting the video; determining an order of determining at least one largest coding unit in the at least one processing block; determining at least one largest coding unit on the basis of the determined order; and decoding the determined at least one largest coding unit, wherein the order is one of a plurality of orders for determining a largest coding unit.

Abstract: Provided is a method of decoding a video according to an embodiment, the method including determining at least one processing block for splitting the video; determining an order of determining at least one largest coding unit in the at least one processing block; determining at least one largest coding unit on the basis of the determined order; and decoding the determined at least one largest coding unit, wherein the order is one of a plurality of orders for determining a largest coding unit.

Abstract: Provided is a method of decoding a video according to an embodiment, the method including determining at least one processing block for splitting the video; determining an order of determining at least one largest coding unit in the at least one processing block; determining at least one largest coding unit on the basis of the determined order; and decoding the determined at least one largest coding unit, wherein the order is one of a plurality of orders for determining a largest coding unit.

Abstract: Provided is a method of decoding a video according to an embodiment, the method including determining at least one processing block for splitting the video; determining an order of determining at least one largest coding unit in the at least one processing block; determining at least one largest coding unit on the basis of the determined order; and decoding the determined at least one largest coding unit, wherein the order is one of a plurality of orders for determining a largest coding unit.

Abstract: Provided is a method of decoding a video according to an embodiment, the method including determining at least one processing block for splitting the video; determining an order of determining at least one largest coding unit in the at least one processing block; determining at least one largest coding unit on the basis of the determined order; and decoding the determined at least one largest coding unit, wherein the order is one of a plurality of orders for determining a largest coding unit.

Abstract: The present invention provides artificial intelligence technology which has machine-learning-based information understanding capability, including metric learning providing improved classification performance, classification of an object considering a semantic relationship, understanding of the meaning of a scene based on the metric learning and the classification, and the like. An electronic device according to one embodiment of the present invention comprises a memory in which at least one instruction is stored, and a processor for executing the stored instruction. Here, the processor extracts feature data from training data of a first class, obtains a feature point by mapping the extracted feature data to an embedding space, and makes an artificial neural network learn in a direction for reducing a distance between the obtained feature point and an anchor point.

Abstract: Provided is a method of decoding an image, the method including: determining at least one prediction unit included in a current frame that is one of at least one frame forming the image; determining a reference region to be referred to by a current prediction unit that is one of the at least one prediction unit; changing a sample value included in at least one of the current prediction unit and the reference region, based on an analyzing result of a sample value of the reference region; determining a sample value included in the current prediction unit, based on a result of changing the sample value; and decoding the image based on the determined sample value of the current prediction unit.

Abstract: Provided is a method of decoding an image, the method including: determining at least one prediction unit included in a current frame that is one of at least one frame forming the image; determining a reference region to be referred to by a current prediction unit that is one of the at least one prediction unit; changing a sample value included in at least one of the current prediction unit and the reference region, based on an analyzing result of a sample value of the reference region; determining a sample value included in the current prediction unit, based on a result of changing the sample value; and decoding the image based on the determined sample value of the current prediction unit.

Abstract: Provided is a method of decoding an image, the method including: determining at least one prediction unit included in a current frame that is one of at least one frame forming the image; determining a reference region to be referred to by a current prediction unit that is one of the at least one prediction unit; changing a sample value included in at least one of the current prediction unit and the reference region, based on an analyzing result of a sample value of the reference region; determining a sample value included in the current prediction unit, based on a result of changing the sample value; and decoding the image based on the determined sample value of the current prediction unit.

Abstract: Provided is a method of decoding an image, the method including: determining at least one prediction unit included in a current frame that is one of at least one frame forming the image; determining a reference region to be referred to by a current prediction unit that is one of the at least one prediction unit; changing a sample value included in at least one of the current prediction unit and the reference region, based on an analyzing result of a sample value of the reference region; determining a sample value included in the current prediction unit, based on a result of changing the sample value; and decoding the image based on the determined sample value of the current prediction unit.

Abstract: Provided is a method of decoding a video according to an embodiment, the method including determining at least one processing block for splitting the video; determining an order of determining at least one largest coding unit in the at least one processing block; determining at least one largest coding unit on the basis of the determined order; and decoding the determined at least one largest coding unit, wherein the order is one of a plurality of orders for determining a largest coding unit.

Abstract: Provided is a method of decoding a video according to an embodiment, the method including determining at least one processing block for splitting the video; determining an order of determining at least one largest coding unit in the at least one processing block; determining at least one largest coding unit on the basis of the determined order; and decoding the determined at least one largest coding unit, wherein the order is one of a plurality of orders for determining a largest coding unit.

Abstract: Provided is a method of decoding a video according to an embodiment, the method including determining at least one processing block for splitting the video; determining an order of determining at least one largest coding unit in the at least one processing block; determining at least one largest coding unit on the basis of the determined order; and decoding the determined at least one largest coding unit, wherein the order is one of a plurality of orders for determining a largest coding unit.

Abstract: Provided is an image predicting method including: obtaining a plurality of adjacent samples located adjacent to a current block; determining an adjacent sample as a reference sample to be referred to by a current sample, the adjacent sample being from among the plurality of adjacent samples and being indicated by a direction of an intra mode of the current block; and adjusting a sample value of the reference sample according to a reference distance indicating a distance between the reference sample and the current sample, and determining a prediction value of the current sample based on the adjusted sample value of the reference sample.

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: A method and system for controlling motor driven power steering are provided. The system includes a magnetic field generation detection module that detects generation of a magnetic field upon operating an electric part of a vehicle and a torque offset determination unit that determines whether a temporary torque offset has occurred in a torque to be applied to a motor based on a detection signal of the magnetic field generation detection module. A torque offset correction unit then corrects the torque offset to a normal torque range based on a torque offset correction logic in response to determining that the torque offset has occurred.

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.

Abstract: Provided is a method of decoding an image, the method including: determining at least one prediction unit included in a current frame that is one of at least one frame forming the image; determining a reference region to be referred to by a current prediction unit that is one of the at least one prediction unit; changing a sample value included in at least one of the current prediction unit and the reference region, based on an analyzing result of a sample value of the reference region; determining a sample value included in the current prediction unit, based on a result of changing the sample value; and decoding the image based on the determined sample value of the current prediction unit.

Abstract: Provided is a method of decoding an image, the method including: determining at least one prediction unit included in a current frame that is one of at least one frame forming the image; determining a reference region to be referred to by a current prediction unit that is one of the at least one prediction unit; changing a sample value included in at least one of the current prediction unit and the reference region, based on an analyzing result of a sample value of the reference region; determining a sample value included in the current prediction unit, based on a result of changing the sample value; and decoding the image based on the determined sample value of the current prediction unit.

Abstract: Provided is a method of decoding an image, the method including: determining at least one prediction unit included in a current frame that is one of at least one frame forming the image; determining a reference region to be referred to by a current prediction unit that is one of the at least one prediction unit; changing a sample value included in at least one of the current prediction unit and the reference region, based on an analyzing result of a sample value of the reference region; determining a sample value included in the current prediction unit, based on a result of changing the sample value; and decoding the image based on the determined sample value of the current prediction unit.