[https: xtruet.github.io ,托管于github](https: xtruet.github.io %EF%BC%8C%E6%89%98%E7%AE%A1%E4%BA%8Egithub) pages依赖于jekyll的个人博客
[https: xtruet.github. io, hosted in github] (https: xtruet.github. io% EF% BC% 8C% E6% 89% 98% E7% AE% A1% E4% BA% 8Egithub) Pages rely on jekyll s personal blog (2023-11-02, HTML, 0KB, 下载0次)
Bugs框架，
Bugs Framework, (2023-10-14, HTML, 0KB, 下载0次)
bf.pages.dev文件
bf.pages.dev (2023-07-13, HTML, 0KB, 下载0次)
柴油机，E10，E5 Preisver nderung，德国，
Diesel, E10, E5 Preisver nderung in Deutschland, (2023-07-13, HTML, 0KB, 下载0次)
用于Hackintosh的EFI:Huanzhi F8、Intel Xeon E5-26XX V4（Broadwell HEDT）和RX 580 8Gb或其他兼容GPU。
EFI for Hackintosh: Huananzhi F8, Intel Xeon E5-26XX V4 (Broadwell HEDT) and RX 580 8Gb or others compatible GPUs. (2022-01-28, HTML, 25613KB, 下载0次)
用于Hackintosh的EFI:Huanzhi F8、Intel Xeon E5-26XX V3（Haswell HEDT）和RX 580 8Gb
EFI for Hackintosh: Huananzhi F8, Intel Xeon E5-26XX V3 (Haswell HEDT) and RX 580 8Gb (2022-12-04, HTML, 27302KB, 下载0次)
使用LLVM的BrainF**k编译器教程
BrainF**k Compiler Tutorial with LLVM (2016-03-19, HTML, 42KB, 下载0次)
A1基础数据分析，，
A1-basic-data-analysis,, (2015-05-27, HTML, 32720KB, 下载0次)
该存储库仅包含基于最新Betaflight（4.3）版本的处理图表
This repository contains only processing charts based on latest Betaflight (4.3) version (2022-09-06, HTML, 1205KB, 下载0次)
基于云访问Eurex和Xetra的高质量逐单历史市场数据
Cloud-based access to high-quality order-by-order historical market data from Eurex and Xetra (2021-01-05, HTML, 1343KB, 下载0次)
[http: m.maizuo.com v4 co=maizuo卖座网vue的实现](http: m.maizuo.com v4 co=maizuo%E5%8D%96%E5%BA%A7%E7%BD%91vue%E7%9A%84%E5%AE%9E%E7%8E%B0)
[http: m.maizuo.com v4 co=the realization of maizuo sales base network vue] (http: m.maizuo.com v4 co=maizuo% E5% 8D% 96% E5% BA% A7% E7% BD% 91vue% E7% 9A% 84% E5% AE% 9E% E7% 8E% B0) (2017-11-13, HTML, 255KB, 下载0次)
很棒的书-E6，，
Awesome-books-E6,, (2023-02-21, HTML, 555KB, 下载0次)
本回购包含Seeed Studio LoRa-E5企鹅羽毛的所有必要设计和制造文件...
This repo contains all the necessary design and fabrication files for the Seeed Studio LoRa-E5 based Penguino Feather breakout board. (2021-05-30, HTML, 9189KB, 下载0次)
以前介绍过很多次的一个分析 HTML 页面 DOM 树并生成非常漂亮元素连接图的应用 Websites as Graphs([http: www.aharef.info static htmlgraph),很可惜,现在这个网站已经无法...](http: www.aharef.info static htmlgraph%EF%BC%89%EF%BC%8C%E5%BE%88%E5%8F%AF%E6%83%9C%EF%BC%8C%E7%8E%B0%E5%9C%A8%E8%BF%99%E4%B8%AA%E7%BD%91%E7%AB%99%E5%B7%B2%E7%BB%8F%E6%97%A0%E6%B3%95%E8%AE%BF%E9%97%AE%E4%BA%86%E3%80%82%E6%9C%AC%E9%A1%B5%E9%9D%A2%E5%9F%BA%E4%BA%8E)
I have introduced an application called Websites as Graphs that analyzes HTML page DOM trees and generates very beautiful element connection graphs many times before. Unfortunately, this website is no longer able to (http: www.aharef-info static htmlgraph% EF% BC% 89% EF% BC% 8C% E5% BE% 88% E5% 8F% AF% E6% 83% 9C% EF% BC% 8C% E7% 8E% B0% E5% 9C% A8% E8% BF% 99% E4% B8% AA% E7% BD% 91% E7% AB% 99% E5% B7% B2% E7% BB% 8F% E6% 97% A0% E6% B3% 95% E8% AE% BF% E9% 97% AE% E4% BA% 86% E3% 80% 82% E6% 9C% AC% E9% A1% B5% E9% 9D% A2% E5% 9F% BA% E4% BA% 8E) (2016-08-26, HTML, 75KB, 下载0次)
Chrome几枝插件([https: github.com unicar9 jizhi)网页版](https: github.com unicar9 jizhi%EF%BC%89%E7%BD%91%E9%A1%B5%E7%89%88)
Several Chrome plugins ([https: github. com unicar9 jizhi) web version] (https: github. com unicar9 jizhi% EF% BC% 89% E7% BD% 91% E9% A1% B5% E7% 89% 88) (2019-12-10, HTML, 3384KB, 下载0次)
建立一个交通标志识别项目，该数据集有超过50000张43类的图像。我能够重新...
Building a Traffic Sign Recognition Project, This dataset has more than 50,000 images of 43 classes. I was able to reach a 98.889% validation accuracy, and a 97.2% testing accuracy. (2019-05-06, HTML, 8408KB, 下载0次)
在Nexys A7 100T FPGA上实现的高精度数字时钟，配有可调节的显示亮度和时间...
High accuracy digital clock implemented on a Nexys A7 100T FPGA complete with adjustable display brightness and time controls including reset, and time setting. (2021-04-30, HTML, 2277KB, 下载0次)
基于MongoDB的全栈Flask里程碑项目||得分：97%
Full Stack MongoDB-based Flask Milestone Project|| Score: 97% (2021-03-20, HTML, 5070KB, 下载0次)
编程实践网络集群A1
Praktikum Pemograman Web Cluster A1 (2020-12-14, HTML, 3KB, 下载0次)
德国交通标志分类使用TensorFlow，在这个项目中，我使用Python和TensorFlow对交通标志进行分类。使用的数据集：德国交通标志数据集。T...
In this project, I used Python and TensorFlow to classify traffic signs. Dataset used: German Traffic Sign Dataset. This dataset has more than 50,000 images of 43 classes. I was able to reach a +99% validation accuracy, and a 97.3% testing accuracy. (2019-12-03, HTML, 8970KB, 下载0次)