Abstract:
An image processing techniques and apparatuses providing image analysis that calculates a feature value of an input frame image; compares the feature value of the frame image with a feature value of a previous frame image or standard frame image to determine an area corresponding to a change of the feature value and a degree of the change of the feature value in the input frame image. A color-coded display of the corresponding area may be generated based on the degree of change.
Abstract:
A method of generating a model for image processing includes increasing, using a receptive field (RF) increasing module of at least one processor, a receptive field of an input image frame; generating, using a feature extraction (FE) module of the at least one processor, a feature map based on the input image frame with an increased receptive field; generating, using a super resolution (SR) module of the at least one processor, a target image having a target resolution, based on the feature map; and generating, using a model generation (MG) module of the at least one processor, a replacement model that replaces at least one of the RF increasing module, the FE module, and the SR module.
Abstract:
A video processing method is provided. The video processing method obtaining a clip representation based on a frame index and a global representation of an input video, obtaining a residual frame representation based on the frame index and a residual representation of the input video using a residual neural network and outputting a final frame representation generated based on the clip representation and the residual frame representation.
Abstract:
An apparatus that supports a rehabilitation of a brain-damaged patient, including a patient condition analyzer configured to generate a patient condition scenario about a brain condition of a patient based on brain-related information of the patient, a network model determiner configured to determine a network model to be applied to the patient using the patient condition scenario, and a rehabilitation model generator configured to generate a rehabilitation model to be applied to the patient based on the determined network model.