<?xml version="1.0" encoding="utf-8" standalone="yes"?><rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>Seungkyun Hong* | 안성현</title><link>https://skiddieahn.github.io/ko/authors/seungkyun-hong/</link><atom:link href="https://skiddieahn.github.io/ko/authors/seungkyun-hong/index.xml" rel="self" type="application/rss+xml"/><description>Seungkyun Hong*</description><generator>Source Themes Academic (https://sourcethemes.com/academic/)</generator><language>ko-kr</language><lastBuildDate>Thu, 01 Aug 2024 00:00:00 +0000</lastBuildDate><image><url>https://skiddieahn.github.io/images/icon_huf1b7dbdf264b64ccae67ec7e89477a75_22677_512x512_fill_lanczos_center_3.png</url><title>Seungkyun Hong*</title><link>https://skiddieahn.github.io/ko/authors/seungkyun-hong/</link></image><item><title>Making Anomalies More Anomalous: Video Anomaly Detection Using a Novel Generator and Destroyer</title><link>https://skiddieahn.github.io/ko/publication/ieee-access-2024/</link><pubDate>Thu, 01 Aug 2024 00:00:00 +0000</pubDate><guid>https://skiddieahn.github.io/ko/publication/ieee-access-2024/</guid><description/></item><item><title>Dual Stream Fusion U-Net Transformers for 3D Medical Image Segmentation</title><link>https://skiddieahn.github.io/ko/publication/bigcomp-2024/</link><pubDate>Thu, 01 Feb 2024 00:00:00 +0000</pubDate><guid>https://skiddieahn.github.io/ko/publication/bigcomp-2024/</guid><description/></item></channel></rss>