Abstract: A variety of exemplary embodiments for processing images are disclosed. In an exemplary embodiment, an image processing method includes a step of extracting a first face feature from an input image including a first face image, a step of generating a second face feature by combining the extracted first face feature with a virtual face feature, a step of generating a second face image on the basis of the generated second face feature, and a step of generating an output image by substantially replacing the first face image with the generated second face image in the input image.

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). The present invention relates to a method and an apparatus in a communication system. A method of a network node in the communication system comprises the steps of: measuring at least one factor value indicating channel link performance of a channel link between the network node and another network node; identifying a beamforming training scheme based on the at least one factor value; and performing beamforming training with the another network node by means of the selected beamforming training method, thereby finding an optimal beam for maintaining services through the most efficient method according to a channel state and minimizing the time consumed for beamforming training.

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). The present invention relates to a method and an apparatus in a communication system. A method of a network node in the communication system comprises the steps of: measuring at least one factor value indicating channel link performance of a channel link between the network node and another network node; identifying a beamforming training scheme based on the at least one factor value; and performing beamforming training with the another network node by means of the selected beamforming training method, thereby finding an optimal beam for maintaining services through the most efficient method according to a channel state and minimizing the time consumed for beamforming training.