What is he best known for?
The fields of study Bodo Rosenhahn is best known for:
- Computer vision
- Euclidean space
- Computer graphics (images)
Bodo Rosenhahn applies the principles of Point (geometry) and Conformal map in his work under Geometry.
Bodo Rosenhahn incorporates Point (geometry) and Geometry in his studies.
Among his research on Inertial frame of reference, you can see a combination of other fields of science like Inertial measurement unit and Quantum mechanics.
He integrates Quantum mechanics with Inertial frame of reference in his research.
Artificial intelligence is closely attributed to Inertial measurement unit in his research.
His Computer vision study typically links adjacent topics like Monocular.
While working in this field, Bodo Rosenhahn studies both Algorithm and Mathematical optimization.
Borrowing concepts from Algorithm, he weaves in ideas under Mathematical optimization.
His Artificial intelligence research extends to Pattern recognition (psychology), which is thematically connected.
His most cited work include:
- Recovering Accurate 3D Human Pose in the Wild Using IMUs and a Moving Camera (325 citations)
- Optimization and Filtering for Human Motion Capture (204 citations)
- Sparse Inertial Poser: Automatic 3D Human Pose Estimation from Sparse IMUs (148 citations)
What are the main themes of his work throughout his whole career to date
Bodo Rosenhahn performs multidisciplinary study on Artificial intelligence and Theoretical computer science in his works.
Bodo Rosenhahn performs multidisciplinary study in Computer vision and Algorithm in his work.
With his scientific publications, his incorporates both Algorithm and Computer vision.
His research ties Tracking (education) and Pedagogy together.
His Tracking (education) study often links to related topics such as Pedagogy.
As part of his studies on Motion (physics), he often connects relevant areas like Motion capture.
His Motion capture study often links to related topics such as Motion (physics).
His Segmentation study frequently draws connections between adjacent fields such as Image segmentation.
Image segmentation connects with themes related to Segmentation in his study.
Bodo Rosenhahn most often published in these fields:
- Artificial intelligence (89.62%)
- Computer vision (65.09%)
- Pattern recognition (psychology) (34.91%)
What were the highlights of his more recent work (between 2019-2022)?
- Artificial intelligence (90.00%)
- Programming language (40.00%)
- Computer vision (40.00%)
In recent works Bodo Rosenhahn was focusing on the following fields of study:
Programming language is intertwined with Path (computing), Process (computing), Extension (predicate logic) and Set (abstract data type) in his research.
The study of Process (computing) is intertwined with the study of Programming language in a number of ways.
He links relevant research areas such as Orientation (vector space), Block (permutation group theory) and Reduction (mathematics) in the realm of Geometry.
The study of Reduction (mathematics) is intertwined with the study of Geometry in a number of ways.
His Image (mathematics) study falls within the topics of Closed captioning and Aerial image.
His Image (mathematics) research extends to Aerial image, which is thematically connected.
Microscopy, Contrast (vision) and Focus (optics) are all intertwined in Optics research.
Bodo Rosenhahn integrates several fields in his works, including Focus (optics) and Optics.
His Operating system study frequently draws connections to other fields, such as Encoder and Path (computing).
Between 2019 and 2022, his most popular works were:
- AMENet: Attentive Maps Encoder Network for trajectory prediction (18 citations)
- Image Captioning Through Image Transformer (15 citations)
- Animal models and animal-free innovations for cardiovascular research: current status and routes to be explored. Consensus document of the ESC Working Group on Myocardial Function and the ESC Working Group on Cellular Biology of the Heart (14 citations)
In his most recent research, the most cited works focused on:
- Transformer
- Voltage
- Machine learning
His work blends Artificial intelligence and Machine learning studies together.
In his works, Bodo Rosenhahn performs multidisciplinary study on Machine learning and Generative model.
His research on Trajectory frequently links to adjacent areas such as Astronomy.
His Astronomy study frequently draws connections to adjacent fields such as Trajectory.
His Encoder research extends to the thematically linked field of Operating system.
As part of his studies on Encoder, Bodo Rosenhahn frequently links adjacent subjects like Operating system.
His research combines Artificial intelligence and Motion (physics).
His Generative grammar study frequently draws connections to adjacent fields such as Generative model.
His research brings together the fields of Path (computing) and Programming language.
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