Timm Linder

899 citations
17 papers · 309 · h-index 9

Impact in

Papers in

Timm Linder

15 papers receiving 298 citations

Peers

Timm Linder
Comparison fields: 5 of 60
  • Computer Vision and Pattern Recognition 198
  • Human-Computer Interaction 22
  • Automotive Engineering 41
  • Artificial Intelligence 65
  • Information Systems 41
Replace Stefano Alletto with:
Stefano Alletto Italy
Junho Seo South Korea
Bima Sena Bayu Dewantara Indonesia
Nathaniel Bird United States
Korbinian Frank Germany
Mohd Ezanee Rusli Malaysia
Samantha Rajapaksha Sri Lanka
Mario Ortí Mata Spain
Lúcio F. Vismari Brazil
Timm Linder relative to Stefano Alletto Italy Stefano Alletto's profile →
Citations per field
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Stefano Alletto · 1×
Citations per year

Countries citing papers authored by Timm Linder

Since Specialization
Citations

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

Fields of papers citing papers by Timm Linder

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 21 scholars most cited alongside Timm Linder, 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 Timm Linder Line = papers co-authored together Timm Linder links everyone, so they are left out of the graph.

All Works

17 of 17 papers shown
#Work
1 201680
2
MeTRAbs: Metric-Scale Truncation-Robust Heatmaps for Absolute 3D Human Pose Estimation
202153
3 201240
4 202025
5 201825
6
Multi-model hypothesis tracking of groups of people in RGB-D data
201421
7 201521
8 20119
9 20219
10 20157
11 20246
12 20236
13 20243
14
Context-aware Recommendations on Rails
20133
15 20251
16 20250
17 20250

About Timm Linder

Timm Linder is a scholar working on Computer Vision and Pattern Recognition, Human-Computer Interaction, Artificial Intelligence, Biomedical Engineering and Automotive Engineering, having authored 17 papers that have together received 309 indexed citations. Recurring topics across this work include Video Surveillance and Tracking Methods (7 papers), Human Pose and Action Recognition (4 papers), Gait Recognition and Analysis (4 papers), Context-Aware Activity Recognition Systems (2 papers), Anomaly Detection Techniques and Applications (2 papers), Advanced Neural Network Applications (2 papers), Hand Gesture Recognition Systems (2 papers) and Recommender Systems and Techniques (2 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (198 citations), Human-Computer Interaction (22 citations), Automotive Engineering (41 citations), Artificial Intelligence (65 citations) and Information Systems (41 citations). Timm Linder has collaborated with scholars based in Germany, United States and Taiwan. Frequent co-authors include Kai O. Arras, Bastian Leibe, Kai Oliver Arras, Stefan Breuers, Jürgen Ziegler, Narunas Vaškevičius, Sven Wehner, Alexander Hermans, Lucas Beyer and Lucia Pallottino. Their work appears in journals such as IEEE Robotics and Automation Letters, IEEE Robotics & Automation Magazine, User Modeling and User-Adapted Interaction, RWTH Publications (RWTH Aachen) and International Conference on Information Fusion.

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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