Sebastian Ebert

496 citations
29 papers · 373 · h-index 9

Impact in

Papers in

Sebastian Ebert

28 papers receiving 357 citations

Peers

Sebastian Ebert
Comparison fields: 5 of 53
  • Electrical and Electronic Engineering 222
  • Artificial Intelligence 106
  • Renewable Energy, Sustainability and the Environment 45
  • Atomic and Molecular Physics, and Optics 82
  • Computer Vision and Pattern Recognition 40
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Sebastian Ebert relative to Wenjie Li China Wenjie Li's profile →
Citations per field
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Citations per year

Countries citing papers authored by Sebastian Ebert

Since Specialization
Citations

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

Fields of papers citing papers by Sebastian Ebert

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 29 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2014108
2 201375
3 201662
4 201426
5 202219
6 201512
7 198310
8 20168
9 20158
10
CIS-positive: Combining Convolutional Neural Networks and SVMs for Sentiment Analysis in Twitter
20156
11 20105
12 20235
13 20164
14 20213
15 20093
16 20153
17 20242
18 20132
19 20222
20 20122

About Sebastian Ebert

Sebastian Ebert is a scholar working on Artificial Intelligence, Information Systems, Computer Vision and Pattern Recognition, Mechanical Engineering and Electrical and Electronic Engineering, having authored 29 papers that have together received 373 indexed citations. Recurring topics across this work include Topic Modeling (6 papers), Service-Oriented Architecture and Web Services (5 papers), Natural Language Processing Techniques (5 papers), Model-Driven Software Engineering Techniques (4 papers), Sentiment Analysis and Opinion Mining (4 papers), Silicon and Solar Cell Technologies (4 papers), Petri Nets in System Modeling (3 papers) and Handwritten Text Recognition Techniques (3 papers). The work is most often cited by research in Electrical and Electronic Engineering (222 citations), Artificial Intelligence (106 citations), Renewable Energy, Sustainability and the Environment (45 citations), Atomic and Molecular Physics, and Optics (82 citations) and Computer Vision and Pattern Recognition (40 citations). Sebastian Ebert has collaborated with scholars based in Germany and United States. Frequent co-authors include Axel Herguth, Svenja Wilking, Giso Hahn, Hinrich Schütze, Wenpeng Yin, Ngoc Thang Vu, Ulrich Heute, Jasmijn Bastings, Katja Filippova and Polina Zablotskaia. Their work appears in journals such as Pattern Recognition Letters, Solar Energy Materials and Solar Cells, Journal of Applied Physics, Innovations in Systems and Software Engineering and Lecture notes in computer science.

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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