Daniel Göhring

436 total citations
13 papers, 203 citations indexed

About

Daniel Göhring is a scholar working on Aerospace Engineering, Artificial Intelligence and Computer Vision and Pattern Recognition. According to data from OpenAlex, Daniel Göhring has authored 13 papers receiving a total of 203 indexed citations (citations by other indexed papers that have themselves been cited), including 7 papers in Aerospace Engineering, 6 papers in Artificial Intelligence and 5 papers in Computer Vision and Pattern Recognition. Recurrent topics in Daniel Göhring's work include Robotics and Sensor-Based Localization (7 papers), Target Tracking and Data Fusion in Sensor Networks (5 papers) and Indoor and Outdoor Localization Technologies (2 papers). Daniel Göhring is often cited by papers focused on Robotics and Sensor-Based Localization (7 papers), Target Tracking and Data Fusion in Sensor Networks (5 papers) and Indoor and Outdoor Localization Technologies (2 papers). Daniel Göhring collaborates with scholars based in Germany and United States. Daniel Göhring's co-authors include Miao Wang, Hans-Dieter Burkhard, Matthias Jüngel, J. A. Hoffman, Bingyi Cao, Miao Wang, Raúl Rojas, Andreas Philipp, Jan-Erik Hoffmann and Michael Spranger and has published in prestigious journals such as Fundamenta Informaticae, KI - Künstliche Intelligenz and Refubium (Universitätsbibliothek der Freien Universität Berlin).

In The Last Decade

Daniel Göhring

11 papers receiving 182 citations

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name	h						Papers	Cites
Daniel Göhring Germany	6	83	73	63	46	44	13	203
Kay Fuerstenberg Germany	9	45 0.5×	103 1.4×	127 2.0×	52 1.1×	54 1.2×	19	246
Kristopher Kriechbaum United States	6	137 1.7×	106 1.5×	65 1.0×	46 1.0×	33 0.8×	10	244
Jean Laneurit France	8	99 1.2×	79 1.1×	84 1.3×	85 1.8×	72 1.6×	18	236
Arne Suppé United States	8	96 1.2×	152 2.1×	109 1.7×	32 0.7×	59 1.3×	17	265
Zhenglong Guo China	4	83 1.0×	193 2.6×	91 1.4×	36 0.8×	30 0.7×	6	299
Zebang Yang China	3	78 0.9×	187 2.6×	91 1.4×	38 0.8×	30 0.7×	7	289
Jason Ziglar United States	6	98 1.2×	158 2.2×	73 1.2×	21 0.5×	20 0.5×	11	269
Dominik Nuß Germany	10	133 1.6×	131 1.8×	150 2.4×	33 0.7×	86 2.0×	18	294
Hendrik Deusch Germany	8	134 1.6×	112 1.5×	145 2.3×	54 1.2×	129 2.9×	11	310
Trung-Dung Vu France	5	125 1.5×	122 1.7×	101 1.6×	36 0.8×	74 1.7×	5	238

Countries citing papers authored by Daniel Göhring

Since Specialization

Citations

This map shows the geographic impact of Daniel Göhring'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 Göhring with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Daniel Göhring more than expected).

Fields of papers citing papers by Daniel Göhring

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Daniel Göhring. 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 Göhring. The network helps show where Daniel Göhring may publish in the future.

Co-authorship network of co-authors of Daniel Göhring

This figure shows the co-authorship network connecting the top 25 collaborators of Daniel Göhring. A scholar is included among the top collaborators of Daniel Göhring based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Daniel Göhring. Daniel Göhring is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

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13 of 13 papers shown

1.

Cao, Bingyi, et al.. (2021). LiDAR-Based Object-Level SLAM for Autonomous Vehicles. 2021 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS). 4397–4404. 7 indexed citations

2.

Cao, Bingyi, et al.. (2020). Accurate Localization of Autonomous Vehicles Based on Pattern Matching and Graph-Based Optimization in Urban Environments. 1–6. 10 indexed citations

3.

Göhring, Daniel, et al.. (2020). Pedestrian Head and Body Pose Estimation with CNN in the Context of Automated Driving. 353–360. 2 indexed citations

4.

Göhring, Daniel, et al.. (2011). Radar/Lidar sensor fusion for car-following on highways. Refubium (Universitätsbibliothek der Freien Universität Berlin). 407–412. 99 indexed citations

5.

Wang, Miao, et al.. (2011). iDriver - Human Machine Interface for Autonomous Cars. Refubium (Universitätsbibliothek der Freien Universität Berlin). 435–440. 13 indexed citations

6.

Göhring, Daniel. (2010). Constraint Based World Modeling for Multi Agent Systems in Dynamic Environments. KI - Künstliche Intelligenz. 24(4). 349–353.

7.

Göhring, Daniel, et al.. (2009). Constraint based world modeling in mobile robotics. 2538–2543. 4 indexed citations

8.

Göhring, Daniel, et al.. (2008). Constraint Based World Modeling. Fundamenta Informaticae. 85(1). 123–137. 1 indexed citations

9.

Göhring, Daniel & Hans-Dieter Burkhard. (2007). CooperativeWorld Modeling in Dynamic Multi-Robot Environments. Fundamenta Informaticae. 75(1). 281–294. 3 indexed citations

10.

Hild, Manfred, et al.. (2007). How to Get from Interpolated Keyframes to Neural Attractor Landscapes and Why.. 1 indexed citations

11.

Göhring, Daniel & Hans-Dieter Burkhard. (2006). Multi Robot Object Tracking and Self Localization Using Visual Percept Relations. 3276. 31–36. 27 indexed citations

12.

Hoffmann, Jan-Erik, et al.. (2006). Further studies on the use of negative information in mobile robot localization. 3276. 62–67. 5 indexed citations

13.

Hoffman, J. A., et al.. (2005). Making use of what you don't see: negative information in Markov localization. 5429. 2947–2952. 31 indexed citations

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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