Person Type: Students

169 to 174 of 680

28FEB 2023
News
Join our Pattern Recognition Symposium
We are thrilled to announce our upcoming Pattern Recognition Symposium, taking place from Monday, March 6th to Friday, March 10th. This is an exciting opportunity for researchers, practitioners, and students to come together and explore the latest advancements in the field of pattern recognition. Our symposium will be held online, with public presentations streamed via […]
Read more about Join our Pattern Recognition Symposium
03FEB 2023
Competitions
ICDAR2023 Competition on Detection and Recognition of Greek Letters on Papyri
This competition investigates the performance of glyph detection and recognition on a very challenging type of historical document: Greek papyri. The detection and recognition of Greek letters on papyri is a preliminary step for computational analysis of handwriting that can lead to major steps forward in our understanding of this major source of information on […]
Read more about ICDAR2023 Competition on Detection and Recognition of Greek Letters on Papyri
02FEB 2023
News
Finalist for KI-Newcomer*innen Award 2023
Nora Gourmelon, a PhD student at the Pattern Recognition Lab, is one of three finalists for the 2023 AI Newcomer Award in the field of natural and life sciences.This award is granted by the German Association of Computer Science (Gesellschaft für Informatik) to young researchers under 30 years for innovative developments in the area of […]
Read more about Finalist for KI-Newcomer*innen Award 2023
16JAN 2023
Ph.D. Gallery
Christoph Seeger
Obstacle Fusion and Scene Interpretation for Autonomous Driving with Occupancy Grids Autonomous driving is, besides electrification, currently one of the most competitiveareas in the automotive industry. A substantially challenging part of autonomousvehicles is the reliable perception of the driving environment. This dissertation isconcerned with improving the sensor-based perception and classification of the staticdriving environment. In […]Obstacle Fusion and Scene Interpretation for Autonomous Driving with Occupancy Grids Autonomous driving is, besides electrification, currently one of the most competitiveareas in the automotive industry. A substantially challenging part of autonomousvehicles is the reliable perception of the driving environment. This dissertation isconcerned with improving the sensor-based perception and classification of the staticdriving environment. In […]
Read more about Christoph Seeger
16JAN 2023
Ph.D. Gallery
<strong>Matthias Utzschneider </strong>
Acquisition- and Reconstruction-Techniques for Sodium Quantification in the Skeletal Muscle using Sodium Magnetic Resonance Imaging (23Na MRI) Measurement of the tissue sodium concentration (TSC) in human tissue offers important insights into pathological- and biological processes with applications in nephrology, neurology and myology. The TSC can be determined non-invasively by sodium magnetic resonance imaging (23Na MRI). […]Acquisition- and Reconstruction-Techniques for Sodium Quantification in the Skeletal Muscle using Sodium Magnetic Resonance Imaging (23Na MRI) Measurement of the tissue sodium concentration (TSC) in human tissue offers important insights into pathological- and biological processes with applications in nephrology, neurology and myology. The TSC can be determined non-invasively by sodium magnetic resonance imaging (23Na MRI). […]
Read more about <strong>Matthias Utzschneider </strong>
16JAN 2023
Ph.D. Gallery
<strong>Juan Camilo Vasquez Correa</strong>
Multimodal Assessment of Parkinson’s Disease Patients using Information from Speech, Handwriting, and Gait The automatic analysis of different bio-signals from patients with Parkinson’s disease is a highly relevant topic that has been addressed by the research community within several years. Identifying bio-markers for early and differential diagnosis, severity assessment, and response to therapy is a […]Multimodal Assessment of Parkinson’s Disease Patients using Information from Speech, Handwriting, and Gait The automatic analysis of different bio-signals from patients with Parkinson’s disease is a highly relevant topic that has been addressed by the research community within several years. Identifying bio-markers for early and differential diagnosis, severity assessment, and response to therapy is a […]
Read more about <strong>Juan Camilo Vasquez Correa</strong>