<rss xmlns:atom="http://www.w3.org/2005/Atom" version="2.0"><channel><title>Self-made Project - Tag - Zhiverse</title><link>https://yao-chih.netlify.app/en/tags/self-made-project/</link><description>Self-made Project - Tag - Zhiverse</description><generator>Hugo -- gohugo.io</generator><language>en</language><managingEditor>yaochihh@gmail.com (Josh)</managingEditor><webMaster>yaochihh@gmail.com (Josh)</webMaster><copyright>Zhiverse</copyright><atom:link href="https://yao-chih.netlify.app/en/tags/self-made-project/" rel="self" type="application/rss+xml"/><item><title>CNN Image Recognition Experiment</title><link>https://yao-chih.netlify.app/en/cnn-image-recognition-experiment/</link><pubDate>Fri, 17 Jul 2026 11:03:26 +0800</pubDate><author>Author</author><guid>https://yao-chih.netlify.app/en/cnn-image-recognition-experiment/</guid><description><![CDATA[<div class="featured-image">
                <img src="https://Josh-test-lab.github.io/posts/CNN%20Image%20Recognition%20Experiment/cover%20image.webp" referrerpolicy="no-referrer">
            </div><p>The cover image was generated by ChatGPT.</p>
<div class="details admonition tip open">
        <div class="details-summary admonition-title">
            <i class="icon fas fa-lightbulb fa-fw" aria-hidden="true"></i>Tip<i class="details-icon fas fa-angle-right fa-fw" aria-hidden="true"></i>
        </div>
        <div class="details-content">
            <div class="admonition-content">This project was written in August 2023. The following content primarily documents my initial experience learning and experimenting with deep learning at that time. As such, some explanations and viewpoints have been preserved to reflect my understanding during that period.</div>
        </div>
    </div>
<p>The year 2023 marked the rapid rise of generative artificial intelligence. From large language models to a wide range of AI-powered applications, artificial intelligence gradually became part of everyday life, making <strong>deep learning</strong> one of the most prominent and widely discussed technologies of the year.</p>
<p>For me, 2023 also marked the beginning of my journey into the world of deep learning, as I built and experimented with my first deep learning models.</p>]]></description></item><item><title>[Thought] Historical Earthquake Locations Around Taiwan</title><link>https://yao-chih.netlify.app/en/historical-earthquake-locations-around-taiwan/</link><pubDate>Wed, 15 Jul 2026 11:03:01 +0800</pubDate><author>Author</author><guid>https://yao-chih.netlify.app/en/historical-earthquake-locations-around-taiwan/</guid><description><![CDATA[<div class="featured-image">
                <img src="https://Josh-test-lab.github.io/posts/Historical%20Earthquake%20Locations%20Around%20Taiwan/cover%20image.webp" referrerpolicy="no-referrer">
            </div><div class="details admonition tip open">
        <div class="details-summary admonition-title">
            <i class="icon fas fa-lightbulb fa-fw" aria-hidden="true"></i>Tip<i class="details-icon fas fa-angle-right fa-fw" aria-hidden="true"></i>
        </div>
        <div class="details-content">
            <div class="admonition-content">This project was written in January 2026.</div>
        </div>
    </div>]]></description></item><item><title>Historical Typhoon Data Download for Taiwan</title><link>https://yao-chih.netlify.app/en/historical-typhoon-data-download-for-taiwan/</link><pubDate>Mon, 13 Jul 2026 11:03:14 +0800</pubDate><author>Author</author><guid>https://yao-chih.netlify.app/en/historical-typhoon-data-download-for-taiwan/</guid><description><![CDATA[<div class="featured-image">
                <img src="https://Josh-test-lab.github.io/posts/Historical%20Typhoon%20Data%20Download%20for%20Taiwan/cover%20image.jpg" referrerpolicy="no-referrer">
            </div><p>The cover image is a downloaded typhoon satellite image. It is a satellite water vapor cloud image produced by the Central Weather Administration (CWA) using CCU/SSL. The image was captured at 07:10 on July 11, 2026, and was obtained from the Weather Image Archive of the Department of Atmospheric Sciences at Chinese Culture University (Atmospheric Science Research and Application Databank).</p>
<p>This is a small program that was originally written to download typhoon satellite images and related data. Its initial purpose was to collect image data for image recognition research. Since the program was developed at an earlier stage, it still contains several relatively immature implementation approaches. Therefore, this article serves only as a record and reference for the data download process, and does not provide an in-depth discussion of the program architecture or optimization methods. The programming language used in this project is Python.</p>]]></description></item><item><title>Map of Work and School Closures in Taiwan</title><link>https://yao-chih.netlify.app/en/map-of-work-and-school-closures-in-taiwan/</link><pubDate>Sat, 11 Jul 2026 14:39:16 +0800</pubDate><author>Author</author><guid>https://yao-chih.netlify.app/en/map-of-work-and-school-closures-in-taiwan/</guid><description></description></item><item><title>[Forbidden City Project] Building the Forbidden City in Minecraft</title><link>https://yao-chih.netlify.app/en/forbidden-city-project/</link><pubDate>Fri, 03 Jul 2026 15:23:59 +0800</pubDate><author>Author</author><guid>https://yao-chih.netlify.app/en/forbidden-city-project/</guid><description><![CDATA[<div class="featured-image">
                <img src="https://raw.githubusercontent.com/Josh-test-lab/website-assets-repository/refs/heads/main/posts/Forbidden%20City%20Project/cover%20image.png" referrerpolicy="no-referrer">
            </div><p>The Forbidden City, now home to the Palace Museum in Beijing, served as the imperial palace of the Ming and Qing dynasties. It is the largest and best-preserved ancient palace complex in the world, consisting of nearly 10,000 rooms and representing the pinnacle of traditional Chinese imperial architecture.</p>]]></description></item><item><title>Image Compression Tool</title><link>https://yao-chih.netlify.app/en/image-compression-tool/</link><pubDate>Tue, 15 Jul 2025 20:23:26 +0800</pubDate><author>Author</author><guid>https://yao-chih.netlify.app/en/image-compression-tool/</guid><description>&lt;div class="featured-image">
                &lt;img src="https://raw.githubusercontent.com/Josh-test-lab/website-assets-repository/refs/heads/main/posts/Image%20compression%20tool/cover%20image.png" referrerpolicy="no-referrer">
            &lt;/div>在平時建立網站頁面時，我們會發現有時候有些頁面需要讀取一段時間才能出現，而有些頁面卻沒有。經過比較不同網頁後得出一個結論，網頁內的圖片如果大小過大，會造成網頁讀取速度較慢，因此萌生出要找到一款能夠壓縮目前網站目錄下所有圖片工具。但找來找去，網路上都沒有找到合適的應用程式，最後決定自己製作一款能夠壓縮所有圖片的程式。</description></item></channel></rss>