Here you can find an overview of all our currently active L3S projects. Many of our projects are also classified under our research focus areas of Text Mining and Search, Knowledge Graphs and Data Integration, Natural Language Processing, Scene and Video Analysis, and Machine and Deep Learning. They can also be sorted by our focus areas of Manufacturing, Medicine, Science, Security, and Society. See the Project Archive for a list of completed L3S projects.
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Conditional Coding for Learned Image and Video Compression
Machine Learning and Deep Learning | Science
This project deals with learning-based video coding using a meta-learning-based procedure for regularization and dynamic adaptation of the decoder.
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Green AutoML for Driver Assistance Systems
Machine Learning and Deep Learning | Energy & Sustainability
The aim of the GreenAutoML4FAS project is to design a holistic, carbon-efficient system for driver assistance systems

GLACIATION
Machine Learning and Deep Learning | Energy & Sustainability
GLACIATION aims to reduce carbon emissions by developing a distributed knowledge graph that improves the efficiency of big data analysis.
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LUMEN
Knowledge Graphs and Data Integration, Machine Learning and Deep Learning | Science
The LUMEN project is a pioneering initiative to transform cross-domain collaboration and discovery in Mathematics (Maths), Social Sciences and Humanities (SSH), Earth System (ES), and Molecular Dynamics (MD).

Leibniz AI Academy
Machine and Deep Learning, Natural Language Processing and Scene and Video Analysis | Education
Development and establishment of a transcurricular, cross-disciplinary micro-degree program "Leibniz AI Academy" at Leibniz Universität Hannover (LUH).
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NFDI4 Data Science
Knowledge Graphs and Data Integration | Science
NFDI4 Data Science aims to establish a national research data infrastructure in Germany to support all stages of the interdisciplinary research data lifecycle for Data Science and Artificial Intelligence.
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Omnidirectional Videos in VR
Energy & Sustainability
This project aims is for a more lifelike perception of omnidirectional video in VR display systems with increased realism of the displayed content.

OffshorePlan2
| Energy & Sustainability
Complementary using mathematical and event based discrete models for handling complex offshore wind farm installation strategies.

Open Research Knowledge Graph (ORKG)
Knowledge Graphs and Data Integration
ORKG empowers researchers by making knowledge accessible. Discover relevant contributions, explore cutting-edge research, and foster interdisciplinary collaboration.

Online Optimierung
Machine Learning and Deep Learning | Science
The goal of the project is to develop and investigate online convex optimization (OCO)-based control schemes for general cost functions and constraints without relying on restrictive assumptions.
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Real-Action VR
Energy & Sustainability
In this project we set out to pioneer the fully immersive experience of action camera recordings in VR headsets.

Robotics Lab
Machine Learning and Deep Learning | Production, Science
The L3S’s Robot Learning Lab works on foundational research to develop increasingly autonomous assistive systems.

Reflect AI
Science
The project aims to develop hybrid artificial intelligence models that use art-historical expertise and knowledge graphs to improve image similarity assessments in art history.
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SoBigData RI PPP
Text Mining and Search
The SoBigData RI Preparation Phase Project (PPP) is the preparatory phase of the SoBigData RI in the ESFRI RoadMap 2021.

SWIFTT
Machine Learning and Deep Learning | Energy & Sustainability
SWIFTT will provide forest managers with affordable, simple and effective remote sensing tools backed up by powerful machine learning models. It will offer a holistic health monitoring service to detect and map various risks for forests and their managers
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VibroSense
In this project, we will further develop our vibration-based dynamical tactile sensor and integrate it into the Robotic hand of our Praxis partner, Nibotics.
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ZUSE-KI-mobil
Mobility
The ZUSE-KI-mobil project aime to develop an AI accelerator with a flexible, expandable and scalable system-on-chip (SoC) architecture.