Sort by
Refine Your Search
-
Listed
-
Category
-
Program
-
Employer
- Fraunhofer-Gesellschaft
- Nature Careers
- Technical University of Munich
- University of Tübingen
- Leibniz
- Forschungszentrum Jülich
- RWTH Aachen University
- ;
- GFZ Helmholtz Centre for Geosciences
- GFZ Helmholtz-Zentrum für Geoforschung
- Ruhr-Universität Bochum •
- DAAD
- Dresden University of Technology •
- Helmholtz Centre for Environmental Research - UFZ •
- Leibniz Institute of Vegetable and Ornamental Crops
- Ludwig-Maximilians-Universität München •
- Max Planck Institute for Human Cognitive and Brain Sciences •
- Max Planck Institute of Molecular Cell Biology and Genetics, Dresden
- Saarland University •
- Technische Universität München
- University of Bremen •
- 11 more »
- « less
-
Field
-
data to modeling in digital representations to the final visualization and human-machine interaction. We develop modern AI solutions in the areas of 2D/3D image and video understanding, computer vision
-
optical communication networks and systems, as well as machine learning, computer vision and compressing digital videos. Since 2020, Fraunhofer Heinrich Hertz Institute has worked with United Nations
-
such as ecology, economy and social sciences. ZMT aims to use data science tools, including computer vision and deep learning, for the study of rapid changes in tropical coastal socioecological systems
-
age-related macular degeneration (AMD). AMD is the most common cause of vision loss in elderly affecting about 300 million people by 2040. Currently, there is no effective treatment for the majority
-
of computer science or using computer vision methods Excellent knowledge of the development and implementation of methods in the field of digitization, artificial intelligence, machine learning and/or 2D/3D imaging and
-
students who would like to write their final thesis in the field of machine learning / computer vision. The primary goal of this master’s thesis is to develop an algorithm that can accurately and efficiently
-
this knowledge gap and establish improved GHG models accounting for soil invertebrates. To achieve this, we create a rich AI-training dataset for multi-modal inferences, combining computer-vision, environmental
-
planning and control algorithms Multi-modal perception techniques (e.g., vision, tactile, force) Machine learning models for physical behavior prediction and manipulation strategy adaptation Real-world
-
optical communication networks and systems, as well as machine learning, computer vision, and compressing digital videos. Become a part of our team and join our scientific team in the multimedia
-
the institute (e.g., the other research hubs) is expected, as well as an active contribution to creating a modern vision of research on education and its implementation at the institute. Close interdisciplinary