Gihyun Kwon

29 total papers · 721 total citations
6 papers, 126 citations indexed

Gihyun Kwon is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence and Neurology. According to data from OpenAlex, Gihyun Kwon has authored 6 papers receiving a total of 126 indexed citations (citations by other indexed papers that have themselves been cited), including 5 papers in Computer Vision and Pattern Recognition, 3 papers in Artificial Intelligence and 1 paper in Neurology. Recurrent topics in Gihyun Kwon’s work include Domain Adaptation and Few-Shot Learning (2 papers), Generative Adversarial Networks and Image Synthesis (2 papers) and Multimodal Machine Learning Applications (2 papers). Gihyun Kwon is often cited by papers focused on Domain Adaptation and Few-Shot Learning (2 papers), Generative Adversarial Networks and Image Synthesis (2 papers) and Multimodal Machine Learning Applications (2 papers). Gihyun Kwon collaborates with scholars based in South Korea, Japan and Canada. Gihyun Kwon's co-authors include Jong Chul Ye, Dae‐Shik Kim, Minseon Kim, Yongsoo Choi and S. Umehara and has published in prestigious journals such as IEEE Transactions on Pattern Analysis and Machine Intelligence, 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) and Proceedings of the AAAI Conference on Artificial Intelligence.