<?xml version="1.0" encoding="utf-8" standalone="yes"?><rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>Project on CC'Blog</title><link>https://cuicaihao.github.io/project/</link><description>Recent content in Project on CC'Blog</description><generator>Hugo</generator><language>en-AU</language><lastBuildDate>Mon, 27 Apr 2026 00:00:00 +0800</lastBuildDate><atom:link href="https://cuicaihao.github.io/project/index.xml" rel="self" type="application/rss+xml"/><item><title>Split Raster</title><link>https://cuicaihao.github.io/project/split_raster/</link><pubDate>Mon, 27 Apr 2026 00:00:00 +0800</pubDate><guid>https://cuicaihao.github.io/project/split_raster/</guid><description>Break down large image into smaller tiles for Deep Learning and Computer Vision tasks.</description></item><item><title>Enigma – Mission X Challenge Accomplished with Python</title><link>https://cuicaihao.github.io/project/enigma/</link><pubDate>Sat, 20 Apr 2024 00:00:00 +0800</pubDate><guid>https://cuicaihao.github.io/project/enigma/</guid><description>&lt;p&gt;Github Repo: &lt;a href="https://github.com/cuicaihao/Annotated-Transformer-English-to-Chinese-Translator" target="_blank" rel="noreferrer"&gt;https://github.com/cuicaihao/Annotated-Transformer-English-to-Chinese-Translator&lt;/a&gt;&lt;/p&gt;
&lt;h2 id="background" class="relative group"&gt;Background &lt;span class="absolute top-0 w-6 transition-opacity opacity-0 -start-6 not-prose group-hover:opacity-100"&gt;&lt;a class="group-hover:text-primary-300 dark:group-hover:text-neutral-700" style="text-decoration-line: none !important;" href="#background" aria-label="Anchor"&gt;#&lt;/a&gt;&lt;/span&gt;&lt;/h2&gt;&lt;p&gt;Inspired by &lt;a href="https://www.101computing.net/enigma-mission-x-challenge/" target="_blank" rel="noreferrer"&gt;Enigma - Mission X Challenge&lt;/a&gt;, this repo is used to save the research and practice efforts in Different Cipher methods. The primary goals are using python programming language to achieve targets listed as follows:&lt;/p&gt;
&lt;h2 id="dependency" class="relative group"&gt;Dependency &lt;span class="absolute top-0 w-6 transition-opacity opacity-0 -start-6 not-prose group-hover:opacity-100"&gt;&lt;a class="group-hover:text-primary-300 dark:group-hover:text-neutral-700" style="text-decoration-line: none !important;" href="#dependency" aria-label="Anchor"&gt;#&lt;/a&gt;&lt;/span&gt;&lt;/h2&gt;&lt;ul&gt;
&lt;li&gt;python 3.11 (use conda or pyenv)&lt;/li&gt;
&lt;li&gt;pandas&lt;/li&gt;
&lt;li&gt;matplotlib&lt;/li&gt;
&lt;/ul&gt;
&lt;p&gt;Python 3.11 is used for development work, and I believe python version 3.8, 3.9, 3.10 are all OK. FYI, python 3.11 is about 25% faster than 3.10&lt;a href="https://github.com/cuicaihao/python-speedy" target="_blank" rel="noreferrer"&gt;python-speedy&lt;/a&gt; for details.&lt;/p&gt;</description></item><item><title>Deep ConvNets for Oracle Bone Script Recognition with PyTorch and Qt-GUI</title><link>https://cuicaihao.github.io/project/oracle_born_recognition/</link><pubDate>Sun, 03 Apr 2022 00:00:00 +0800</pubDate><guid>https://cuicaihao.github.io/project/oracle_born_recognition/</guid><description>&lt;p&gt;Github Repo:&lt;a href="https://github.com/cuicaihao/Deep-Learning-for-Oracle-Bone-Script-Recognition" target="_blank" rel="noreferrer"&gt;https://github.com/cuicaihao/Deep-Learning-for-Oracle-Bone-Script-Recognition&lt;/a&gt;&lt;/p&gt;
&lt;h2 id="1-project-background" class="relative group"&gt;1. Project Background &lt;span class="absolute top-0 w-6 transition-opacity opacity-0 -start-6 not-prose group-hover:opacity-100"&gt;&lt;a class="group-hover:text-primary-300 dark:group-hover:text-neutral-700" style="text-decoration-line: none !important;" href="#1-project-background" aria-label="Anchor"&gt;#&lt;/a&gt;&lt;/span&gt;&lt;/h2&gt;&lt;p&gt;A short description of the project. This Repository will demonstrate using Pytorch to build deep convolutional neural networks and use Qt to create the GUI with the pre-trained model like the figure below.&lt;/p&gt;
&lt;p&gt;





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 srcset="https://cuicaihao.github.io/project/oracle_born_recognition/OBS_WEB_hu_6d446d7cdfd69df9.webp 330w,https://cuicaihao.github.io/project/oracle_born_recognition/OBS_WEB_hu_9446244f85bf34a2.webp 660w
 
 ,https://cuicaihao.github.io/project/oracle_born_recognition/OBS_WEB_hu_96a8879a540e6fcd.webp 1024w
 
 
 ,https://cuicaihao.github.io/project/oracle_born_recognition/OBS_WEB_hu_7d897b7bf9958aa4.webp 1320w
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 &lt;img
 width="1824"
 height="1396"
 class="mx-auto my-0 rounded-md"
 alt="APP SAMPLE IMAGE"
 loading="lazy" decoding="async"
 
 src="https://cuicaihao.github.io/project/oracle_born_recognition/OBS_WEB_hu_8abd42e00c07b699.jpg" srcset="https://cuicaihao.github.io/project/oracle_born_recognition/OBS_WEB_hu_31bf15393205a6f0.jpg 330w,https://cuicaihao.github.io/project/oracle_born_recognition/OBS_WEB_hu_8abd42e00c07b699.jpg 660w
 
 ,https://cuicaihao.github.io/project/oracle_born_recognition/OBS_WEB_hu_848bab0f45570a71.jpg 1024w
 
 
 ,https://cuicaihao.github.io/project/oracle_born_recognition/OBS_WEB_hu_c6717f0a1ba7afc0.jpg 1320w
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 sizes="100vw"
 
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&lt;/figure&gt;
&lt;/p&gt;</description></item><item><title>Annotated Transformer English-to-Chinese Translator</title><link>https://cuicaihao.github.io/project/annotated-transformer-english-to-chinese-translator/</link><pubDate>Sat, 27 Apr 2019 00:00:00 +0800</pubDate><guid>https://cuicaihao.github.io/project/annotated-transformer-english-to-chinese-translator/</guid><description>A complete PyTorch implementation of the Transformer architecture for English-to-Chinese machine translation, with detailed annotations and step-by-step explanations.</description></item></channel></rss>