What is he best known for?
The fields of study he is best known for:
- Artificial intelligence
- Machine learning
- Gene
Artificial intelligence, Mobile robot, Computer vision, Evolutionary algorithm and Data mining are his primary areas of study.
His Artificial intelligence research includes elements of Machine learning and Pattern recognition.
The concepts of his Mobile robot study are interwoven with issues in Simulation and Motion control.
As part of the same scientific family, Andreas Zell usually focuses on Computer vision, concentrating on Simultaneous localization and mapping and intersecting with Reference image and Feature based.
His studies in Evolutionary algorithm integrate themes in fields like Multi-objective optimization, Point, Theoretical computer science and Fitness function.
His Data mining study integrates concerns from other disciplines, such as Similarity, SBML, Support vector machine, Systems biology and Cluster analysis.
His most cited work include:
- Simulation neuronaler Netze (330 citations)
- SNNS (Stuttgart Neural Network Simulator) (179 citations)
- Automatic Take Off, Tracking and Landing of a Miniature UAV on a Moving Carrier Vehicle (153 citations)
What are the main themes of his work throughout his whole career to date?
His primary areas of investigation include Artificial intelligence, Computer vision, Mobile robot, Robot and Pattern recognition.
Andreas Zell frequently studies issues relating to Machine learning and Artificial intelligence.
Computer vision is closely attributed to Simultaneous localization and mapping in his work.
His biological study deals with issues like Control theory, which deal with fields such as Model predictive control.
His Robot research is multidisciplinary, incorporating perspectives in Ball and Simulation.
His study focuses on the intersection of Support vector machine and fields such as Data mining with connections in the field of Cluster analysis.
He most often published in these fields:
- Artificial intelligence (49.30%)
- Computer vision (26.96%)
- Mobile robot (21.13%)
What were the highlights of his more recent work (between 2014-2021)?
- Artificial intelligence (49.30%)
- Computer vision (26.96%)
- Robot (18.11%)
In recent papers he was focusing on the following fields of study:
His scientific interests lie mostly in Artificial intelligence, Computer vision, Robot, Mobile robot and Algorithm.
His Artificial intelligence research is multidisciplinary, relying on both Machine learning and Pattern recognition.
His study in Computer vision is interdisciplinary in nature, drawing from both Simultaneous localization and mapping, Visual odometry and Benchmark.
His Robot research integrates issues from Ball, Simulation, Human–computer interaction and Modular design.
His study looks at the relationship between Mobile robot and topics such as Motion planning, which overlap with Obstacle avoidance.
He works mostly in the field of Algorithm, limiting it down to topics relating to Occupancy grid mapping and, in certain cases, Matching, as a part of the same area of interest.
Between 2014 and 2021, his most popular works were:
- Multi-camera visual SLAM for autonomous navigation of micro aerial vehicles (45 citations)
- A Distributed Control Approach to Formation Balancing and Maneuvering of Multiple Multirotor UAVs (27 citations)
- Optimizing recurrent reservoirs with neuro-evolution (22 citations)
In his most recent research, the most cited papers focused on:
- Artificial intelligence
- Machine learning
- Gene
His primary scientific interests are in Artificial intelligence, Computer vision, Robot, Mobile robot and Robustness.
Andreas Zell has researched Artificial intelligence in several fields, including Machine learning and Pattern recognition.
In most of his Computer vision studies, his work intersects topics such as Curve fitting.
His research in Robot intersects with topics in Convergence, Multi-agent system, Simulation and Stability theory.
His study in Mobile robot is interdisciplinary in nature, drawing from both Identification, Lookup table, CAD, Particle filter and Structured light.
His work in Particle filter addresses issues such as Probabilistic logic, which are connected to fields such as Data mining.
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