Fraunhofer Institute for Computer Graphics Research IGDLabelledGreenData4All Hackathon
Event details
Location
Über Zoom
Date
January 30, 2025 - February 05, 2025
Topic: "Implementation of Scalable Annotation Strategies Using Case Studies"
Annotated data form the foundation for good model development and serve as a driving force for the advancement of AI-driven environmental research. However, the availability of high-quality, harmonized annotated data is severely limited.
The goal of the LabelledGreenData4All project ("Sustainability Potential Analysis for the Feasibility and Effort of Data Annotations for Machine Learning Models") is to develop strategic recommendations for the environmental sector on which application areas and types of data offer the greatest potential for the use of machine learning (ML) models.
In this hackathon, we will specifically address the challenges faced by AI developers when only a limited amount of labeled data is available for training ML models.
The hackathon consists of three parts.
By registering via the following link, you will receive the access details for the introductory event on January 30, 2025. We look forward to an active exchange!
Project Team
LabelledGreenData4All relies on an interdisciplinary project team that combines expertise from science and research with private sector interests. The wetransform GmbH team and the Fraunhofer Institute for Computer Graphics Research IGD are working together to explore the power of annotated environmental data sets to drive innovation across sectors.
The 12-month research project Nachhaltigkeitspotentialanalyse für die Zweckmäßigkeit und den Aufwand von Datenannotationen für Machine Learning-Modelle [Analysis of Sustainability Potential for the Suitability and Complexity of Data Annotations for Machine Learning Models] from the departmental research plan of the German Federal Ministry for the Environment, Nature Conservation, Nuclear Safety and Consumer Protection is being carried out on behalf of the German Federal Environment Ministry. Project code number: FKZ 3723 11 602 0.