Daniel Beßler

481 citations
9 papers · 235 · h-index 6

Impact in

Papers in

Daniel Beßler

8 papers receiving 220 citations

Peers

Daniel Beßler
Comparison fields: 5 of 45
  • Control and Systems Engineering 108
  • Artificial Intelligence 135
  • Computer Vision and Pattern Recognition 59
  • Industrial and Manufacturing Engineering 28
  • Information Systems 21
Replace Mihai Pomarlan with:
Mihai Pomarlan Germany
Ishika Singh United States
Asil Kaan Bozcuoğlu Germany
Arthur Bucker United Kingdom
Jonathan Styrud Sweden
Matteo Iovino Sweden
Rui Lin China
Tim Niemueller Germany
Jacob Arkin United States
Humbert Fiorino France
Daniel Beßler relative to Mihai Pomarlan Germany Mihai Pomarlan's profile →
Citations per field
00.5×1.5×
Mihai Pomarlan · 1×
Citations per year

Countries citing papers authored by Daniel Beßler

Since Specialization
Citations

This map shows the geographic impact of Daniel Beßler's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Daniel Beßler with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Daniel Beßler more than expected).

Fields of papers citing papers by Daniel Beßler

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Daniel Beßler. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Daniel Beßler. The network helps show where Daniel Beßler may publish in the future.

Co-authors

The 22 scholars most cited alongside Daniel Beßler, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Daniel Beßler Line = papers co-authored together Daniel Beßler links everyone, so they are left out of the graph.

All Works

9 of 9 papers shown
#Work
1 2018111
2 201967
3 202019
4 201818
5 201510
6
Knowledge Representation for Cognition- and Learning-enabled Robot Manipulation
20186
7 20193
8 20241
9 20150

About Daniel Beßler

Daniel Beßler is a scholar working on Artificial Intelligence, Control and Systems Engineering, Computer Vision and Pattern Recognition, Computer Networks and Communications and Molecular Biology, having authored 9 papers that have together received 235 indexed citations. Recurring topics across this work include AI-based Problem Solving and Planning (8 papers), Semantic Web and Ontologies (6 papers), Robotics and Automated Systems (2 papers), Logic, Reasoning, and Knowledge (2 papers), Robotic Path Planning Algorithms (2 papers), Embedded Systems Design Techniques (1 paper), Natural Language Processing Techniques (1 paper) and Multimodal Machine Learning Applications (1 paper). The work is most often cited by research in Control and Systems Engineering (108 citations), Artificial Intelligence (135 citations), Computer Vision and Pattern Recognition (59 citations), Industrial and Manufacturing Engineering (28 citations) and Information Systems (21 citations). Daniel Beßler has collaborated with scholars based in Germany, Spain and United Kingdom. Frequent co-authors include Michael Beetz, Mihai Pomarlan, G. Bartels, Asil Kaan Bozcuoğlu, Jan Rosell, Stefano Borgo, Paulo Gonçalves, Julita Bermejo–Alonso, Marcos Barreto and Howard Li. Their work appears in journals such as The Knowledge Engineering Review, Robotics and Autonomous Systems, KI - Künstliche Intelligenz and Adaptive Agents and Multi-Agents Systems.

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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