Tim Caselitz

620 citations
11 papers · 467 · h-index 6

Impact in

Papers in

Tim Caselitz

11 papers receiving 445 citations

Peers

Tim Caselitz
Comparison fields: 5 of 40
  • Geology 117
  • Computer Vision and Pattern Recognition 297
  • Aerospace Engineering 335
  • Instrumentation 31
  • Environmental Engineering 101
Replace Igor Bogoslavskyi with:
Igor Bogoslavskyi Germany
Ryan W. Wolcott United States
Jan Quenzel Germany
Xiaqing Ding China
Chuanzhe Suo Hong Kong
Yiyang Zhou China
Julian Ryde United States
Ralf Kaestner Switzerland
Yeong Sang Park South Korea
Jintao Xu China
Tim Caselitz relative to Igor Bogoslavskyi Germany Igor Bogoslavskyi's profile →
Citations per field
00.5×1.5×2×
Igor Bogoslavskyi · 1×
Citations per year

Countries citing papers authored by Tim Caselitz

Since Specialization
Citations

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

Fields of papers citing papers by Tim Caselitz

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 10 scholars most cited alongside Tim Caselitz, 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 Tim Caselitz Line = papers co-authored together Tim Caselitz links everyone, so they are left out of the graph.

All Works

11 of 11 papers shown
#Work
1 2016138
2 2016127
3 201683
4 201752
5 201848
6 20147
7 20203
8 20193
9 20183
10 20182
11 20211

About Tim Caselitz

Tim Caselitz is a scholar working on Aerospace Engineering, Geology, Computer Vision and Pattern Recognition, Computer Graphics and Computer-Aided Design and Electrical and Electronic Engineering, having authored 11 papers that have together received 467 indexed citations. Recurring topics across this work include Robotics and Sensor-Based Localization (11 papers), Advanced Vision and Imaging (7 papers), 3D Surveying and Cultural Heritage (5 papers), Indoor and Outdoor Localization Technologies (3 papers), Video Surveillance and Tracking Methods (2 papers), Advanced Image and Video Retrieval Techniques (1 paper), Computer Graphics and Visualization Techniques (1 paper) and Remote Sensing and LiDAR Applications (1 paper). The work is most often cited by research in Geology (117 citations), Computer Vision and Pattern Recognition (297 citations), Aerospace Engineering (335 citations), Instrumentation (31 citations) and Environmental Engineering (101 citations). Tim Caselitz has collaborated with scholars based in Germany and Belgium. Frequent co-authors include Wolfram Burgard, Gian Diego Tipaldi, Bastian Steder, Michael Ruhnke, Rainer Kümmerle, Abhinav Valada, Markus Langer, Rohit Mohan, Gert F. Trommer and Daniel Buscher. Their work appears in journals such as IEEE Robotics and Automation Letters, Robotics and Autonomous Systems, FreiDok plus (Universitätsbibliothek Freiburg) and arXiv (Cornell University).

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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