Lukas Mauch

651 citations
18 papers · 422 · h-index 8

Impact in

Papers in

Lukas Mauch

18 papers receiving 411 citations

Peers

Lukas Mauch
Comparison fields: 5 of 56
  • Building and Construction 81
  • Computer Vision and Pattern Recognition 97
  • Industrial and Manufacturing Engineering 47
  • Renewable Energy, Sustainability and the Environment 70
  • Electrical and Electronic Engineering 203
Replace Meimei Huo with:
Meimei Huo China
Muhammad Bilal Qureshi Pakistan
Zeynep Garip Türkiye
Baihong Jin United States
Musa Yılmaz Türkiye
Abigail Copiaco United Arab Emirates
Subhajit Chatterjee South Korea
Nestor Arana-Arexolaleiba Spain
Ahmad Karim Malaysia
K. Balasubramanian Türkiye
Lukas Mauch relative to Meimei Huo China Meimei Huo's profile →
Citations per field
00.5×6.7×
Meimei Huo · 1×
Citations per year

Countries citing papers authored by Lukas Mauch

Since Specialization
Citations

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

Fields of papers citing papers by Lukas Mauch

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 17 scholars most cited alongside Lukas Mauch, 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 Lukas Mauch Line = papers co-authored together Lukas Mauch links everyone, so they are left out of the graph.

All Works

18 of 18 papers shown
#Work
1 2015152
2 201772
3 201871
4 201646
5 201917
6
Differentiable Quantization of Deep Neural Networks.
201915
7 202012
8 20178
9 20166
10 20175
11 20174
12 20184
13 20232
14 20182
15 20182
16 20182
17 20251
18 20191

About Lukas Mauch

Lukas Mauch is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence, Radiology, Nuclear Medicine and Imaging, Statistical and Nonlinear Physics and Electrical and Electronic Engineering, having authored 18 papers that have together received 422 indexed citations. Recurring topics across this work include Advanced Neural Network Applications (8 papers), Domain Adaptation and Few-Shot Learning (4 papers), Neural Networks and Applications (3 papers), Advanced Image and Video Retrieval Techniques (3 papers), Medical Imaging Techniques and Applications (2 papers), Topic Modeling (2 papers), Advanced MRI Techniques and Applications (2 papers) and Smart Grid Energy Management (2 papers). The work is most often cited by research in Building and Construction (81 citations), Computer Vision and Pattern Recognition (97 citations), Industrial and Manufacturing Engineering (47 citations), Renewable Energy, Sustainability and the Environment (70 citations) and Electrical and Electronic Engineering (203 citations). Lukas Mauch has collaborated with scholars based in Germany, Taiwan and United States. Frequent co-authors include Bin Yang, Thomas Küstner, Fabian Bamberg, Sergios Gatidis, Petros Martirosian, Konstantin Nikolaou, Fritz Schick, Akira Nakamura, Stefan Uhlich and Fabien Cardinaux. Their work appears in journals such as IEEE Journal of Selected Topics in Signal Processing, Journal of the Franklin Institute, Magnetic Resonance Materials in Physics Biology and Medicine, Journal of Electronic Imaging and HAL (Le Centre pour la Communication Scientifique Directe).

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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