<?xml version="1.0" encoding="utf-8" standalone="yes"?><rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>Nuretin Sergin | Hao Yan</title><link>https://hyan46.github.io/authors/nuretin-sergin/</link><atom:link href="https://hyan46.github.io/authors/nuretin-sergin/index.xml" rel="self" type="application/rss+xml"/><description>Nuretin Sergin</description><generator>Wowchemy (https://wowchemy.com)</generator><language>en-US</language><copyright>© 2026 Hao Yan</copyright><lastBuildDate>Fri, 01 Jan 2021 00:00:00 +0000</lastBuildDate><image><url>https://hyan46.github.io/media/icon_hudffdcafa99c609c7e4dfde01dba38f93_35970_512x512_fill_lanczos_center_3.png</url><title>Nuretin Sergin</title><link>https://hyan46.github.io/authors/nuretin-sergin/</link></image><item><title>Edge Computing Accelerated Defect Classification Based on Deep Convolutional Neural Network With Application in Rolling Image Inspection</title><link>https://hyan46.github.io/publication/huang-edge-2021/</link><pubDate>Fri, 01 Jan 2021 00:00:00 +0000</pubDate><guid>https://hyan46.github.io/publication/huang-edge-2021/</guid><description/></item><item><title>Image-Based Process Monitoring via Adversarial Autoencoder with Applications to Rolling Defect Detection</title><link>https://hyan46.github.io/publication/yan-imagebased-2019/</link><pubDate>Thu, 01 Aug 2019 00:00:00 +0000</pubDate><guid>https://hyan46.github.io/publication/yan-imagebased-2019/</guid><description/></item><item><title>Nuretin Dorukhan Sergin</title><link>https://hyan46.github.io/authors/nurretin-sergin/</link><pubDate>Mon, 01 Jan 0001 00:00:00 +0000</pubDate><guid>https://hyan46.github.io/authors/nurretin-sergin/</guid><description>&lt;h1 id="research-interest">Research Interest&lt;/h1>
&lt;p>Develop machine learninng models and efficient real-time large-scale optimization algorithms for high-dimensional data (i.e., Images, profiles, signals) in different industrial systems and spatio-temporal systems for anomaly detection and system modeling&lt;/p></description></item></channel></rss>