"Mensch Ärgere Dich Nicht" mit Java in der JAVA-Vorlesung an der DHBW-Stuttgart TINF16C
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Updated
Jul 21, 2017 - Java
"Mensch Ärgere Dich Nicht" mit Java in der JAVA-Vorlesung an der DHBW-Stuttgart TINF16C
"Mensch Ärgere Dich Nicht" mit JavaFX in der JAVA-Vorlesung an der DHBW-Stuttgart TINF16C
This Python script scrapes relevant information about the DHBW Company's into Excel and onto Google Maps.
Install script for DHBWsoccer database with mariadb on homebrew.
Abschlussprojekt für die C++-Vorlesung. Mensch ärgere dich nicht! über Netzwerk mit Computergegnern.
🚀 Shortest-Paths implementation of Bellman-Ford algorithm in Kotlin
Java project at Cooperative State University Stuttgart Campus Horb. Implements and visualizes Dijkstra algorithm for given map
C# project at Cooperative State University. Application for soccer betting with client and server
Eine Extension zum tracken der Nutzungszeit auf verschiedenen Webseiten.
Big-Data-Project of 6870655 Sem 5 DHBW IT-Automotive 2021
Detect roadway lanes using Python OpenCV for project during the 5th semester at DHBW Stuttgart for lecture in digital image processing.
The project was developed by DHBW students in the 4th semester as part of the elective "PHP". It serves as a small modification of the platform "Twitter" to expand PHP skills.
The main purpose of this web application is the conceptual design and development of a citizen portal with an integrated artificial intelligence during the 3rd and 4th semester at DHBW Stuttgart.
Dieses Repository stellt eine LaTeX-Vorlage für die T-Arbeiten an der DHBW Campus Horb dar.
Cloud Computing Project for the DHBW Stuttgart
This repository is created for the lecture Data Science of the Cooperative State University Stuttgart. It includes some statistics about the page visits and impressions of open data berlin.
This repository is created for the lecture Digital Image Processing of the Cooperative State University Stuttgart. It includes a lane detection for two example videos and different methods.
This repository contains the project of the lecture machine learning of the cooperative state university Stuttgart. The goal is to develop a convolutional neural network (CNN) for image processing. In this project a data set with different emotions of faces in the shape of 80x80 pixels will be trained.
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