Hanseok Ko

TL;DR: A multimodal system is designed that can sense and determine, in real-time, user contextual information, such as where the user is or what the user does, by processing acoustic and visual signals from the suitable sensors available in a mobile device.

TL;DR: A clustering-based dictionary learning method based on a joint patch clustering for multimodal image fusion that requires lower processing time with better fusion quality and the experimental results validate effectiveness.

TL;DR: Experimental results show that the proposed CT image synthesis approach based on a conditional generative adversarial network outperforms other state-of-the-art image synthesis methods with the generated COVID-19 CT images and indicates promising for various machine learning applications including semantic segmentation and classification.

TL;DR: The NTIRE 2020 challenge addresses the real world setting, where paired true high and low-resolution images are unavailable, and the ultimate goal is to achieve the best perceptual quality, evaluated using a human study.

TL;DR: The NTIRE 2020 challenge as discussed by the authors addressed the real world setting, where paired true high and low-resolution images are unavailable, for training, only one set of source input images is provided along with a set of unpaired high-quality target images.