Erhardt Barth

5.6k citations
128 papers · 3.3k · 1 hit paper · h-index 28

Impact in

Papers in

Erhardt Barth

122 papers receiving 3.1k citations

Erhardt Barth's Hit Papers

Explainable COVID-19 Detection Using Chest CT Scans and Deep Learning 2021 · 157 citations
1570+1+3Years since publication50100150

Peers

Erhardt Barth
Comparison fields: 5 of 169
  • Human-Computer Interaction 639
  • Computer Vision and Pattern Recognition 1.6k
  • Instrumentation 146
  • Cognitive Neuroscience 746
  • Health Informatics 41
Replace Thomas Martinetz with:
Thomas Martinetz Germany
Nick Barnes Australia
Yin Li China
Yoichi Sato Japan
Xiaohui Shen United States
Dimitris Samaras United States
Jingyi Yu China
Alexandre Bernardino Portugal
Yiannis Aloimonos United States
Xiongkuo Min China
Erhardt Barth relative to Thomas Martinetz Germany Thomas Martinetz's profile →
Citations per field
00.5×7.3×
Thomas Martinetz · 1×
Citations per year

Countries citing papers authored by Erhardt Barth

Since Specialization
Citations

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

Fields of papers citing papers by Erhardt Barth

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 25 scholars most cited alongside Erhardt Barth, 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 Erhardt Barth Line = papers co-authored together Erhardt Barth links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 128 papers — load more, or switch the sort, to bring in the rest.

#Work
1 1992337
2 2010311
3 2010198
4 2011191
5 2000160
6
Explainable COVID-19 Detection Using Chest CT Scans and Deep Learning
Hit paper breakdown →
2021157
7 1990136
8 2017129
9 2009114
10 201572
11 201962
12 200860
13 200158
14
The importance of intrinsically two-dimensional image features in biological vision and picture coding
199356
15 202047
16 201145
17 202143
18 200939
19 201238
20 200838

About Erhardt Barth

Erhardt Barth is a scholar working on Computer Vision and Pattern Recognition, Human-Computer Interaction, Cognitive Neuroscience, Media Technology and Signal Processing, having authored 128 papers that have together received 3.3k indexed citations. Recurring topics across this work include Gaze Tracking and Assistive Technology (31 papers), Visual perception and processing mechanisms (28 papers), Advanced Vision and Imaging (27 papers), Visual Attention and Saliency Detection (24 papers), Image Processing Techniques and Applications (12 papers), Advanced Image Processing Techniques (10 papers), Computer Graphics and Visualization Techniques (10 papers) and Blind Source Separation Techniques (10 papers). The work is most often cited by research in Human-Computer Interaction (639 citations), Computer Vision and Pattern Recognition (1.6k citations), Instrumentation (146 citations), Cognitive Neuroscience (746 citations) and Health Informatics (41 citations). Erhardt Barth has collaborated with scholars based in Germany, United States and Egypt. Frequent co-authors include Thomas Martinetz, Michael Dörr, Fabian Timm, Christoph Zetzsche, Andreas Kolb, Christoph Linse, Reinhard Koch, Hammam Alshazly, Karl R. Gegenfurtner and Rasmus Larsen. Their work appears in journals such as Neurocomputing, Journal of Vision, Vision Research, IEEE Access and Sensors.

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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