Lando's repositories
alks-scenario-sampler
To assure the quality of an algorithm testing of the algorithm against predefined requirements and validation if the behavior is as expected is necessary. In our case we are testing 15 scenarios given from the ASAM E.V. with a focus on “Automated Lane Keeping Systems.” ASAM E.V. and BMW undertook the task of using OpenSCENARIO and OpenDRIVE standard to implement the ALKS regulatory test program, resulting in an executable XML file package with a standard-compatible simulator. The package can be found on GitHub and is licensed under the create commons CC BY-SA 4.0 and thereby free to use, modify and build on the material for any purpose, even commercial. In detail the xml files describe specific traffic scenarios with various parameter settings like vehicle position, lateral velocity, distance etc. The goal is to vary the variable parameters in a way we gain as much information out of the least amount of experiments.
VolleyTrain
App for Volleyball trainer
university_project_selector
University project to create/choose projects based on React, MySQL und Python
230V_Arduino_Dimmer
Build a board with a TRIAC. Goal is to control 230V lights with Arduino/ESP32
GitHub-Follow-Bot
A python bot to follow GitHub users
Recipe-Text-Analyzer-Multi-Classification
The RTA uses text analytics methods based on an established platform to......identify main ingredients and ingredient combinations in a specific cuisine (e.g. Italian Food, Thai Food etc.)...classify a recipe according to its ingredients
recommendation-dataset
-- Research for google colab import
stock_tracker
A python script that takes an .csv with stock prices and buy date and gives back graphs
tf-gesture-estimation
Gesture esimation /w binary network interaction. Pose Estimation is done via https://github.com/ildoonet/tf-pose-estimation . Then MobileNet & Inception /w retrained final layer to estimate gesture
PyTorch_Pose_Classification
Updated version of https://github.com/leanderpeter/tf-gesture-estimation w/ PyTorch Framework
diabetes_prediction
Using a data set of n=442 patient records to predict the outcome of diabetes medicine. Using a regression in RapidMiner
fluffy-spork
Faculty administration Webapp