other CDE courses
PAISS Artificial Intelligence Summer School 2021
Summary of PAISS Artificial Intelligence Summer School, organized by INRIA and the institutes PRAIRIE and MIAI in July 2019.
2021-07-08
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Summary of PAISS Artificial Intelligence Summer School, organized by INRIA and the institutes PRAIRIE and MIAI in July 2019.
For the EO4GEO Summer School, a project on predicting maize crop yield in Kenya using time series data and a random forest was completed. Our work was presented at the AGIT2021 conference.
Creating a Dashboard, visualizing ICU occupancy rates in the Austrian federal states. A ubuntu 18.04 server hosts an Apache & WSGI installation, which runs a Plotly Dash via Flask. The data is automatically scraped and served via a GeoServer.
The dataset that is worked with consists of roughly individual 40.000 data points of hurricanes. The aim of my workflow is to predict the future speed and bearing of the individual hurricanes using a Neural Network and a Random Forest Regressor. The data will be cleaned, features created and the prediction will be assessed for it’s accuracy as well as the two methods compared.
Using pgRouting, a navigation functionality is implemented based on a spatial database of a fun fair, where the user can input his or her position and be routed to a nearest Point of Interest. A Python DB connector dynamically creates the SQL queries and visualizes the results.
Within the end of term assignment for the Practice of Software Development course, a KML file is created visualizing both the result of an OGC Web Map Service request as well as the parsed information from a CSV file containing tweets and their locations.
Additionally, the tweets are analysed regarding possible profanity and
visualized accordingly.
This blogpost gives short overviews over the topics discussed in the Selected Topics in Geoinformatics Lecture. Instead of summaries of the 10 lectures, brief personal statements and opinions on the topics are given by outlining my personal take-home message from the lectures.
Imagining a relational database for a public bus operator, conceptual and logical databases model are created. The goal is to visualize the entities and their relationships within this scenario.
Using the Sen2Cube semantic query model builder, reductions over both space and time are performed on a semantic cube in order to analyse the average cloud coverage both as an image with pixel based information as well as graphs showing the change over time.
Introduction This assignment deals with an analysis of solar radiation intensity. Since solar power is more in demand than ever due to the increasing demand