Hannes Schulz

2.9k citations
50 papers · 1.1k · h-index 19

Impact in

Papers in

Hannes Schulz

48 papers receiving 1.1k citations

Peers

Hannes Schulz
Comparison fields: 5 of 118
  • Computer Vision and Pattern Recognition 379
  • Artificial Intelligence 365
  • Agronomy and Crop Science 91
  • Soil Science 81
  • Insect Science 94
Replace Thomas Hellström with:
Thomas Hellström Sweden
Henrik Karstoft Denmark
Jinhai Cai Australia
A.-J. Baerveldt Sweden
Tetsuya Shimamura Japan
Luis Emmi Spain
Martin Weis Germany
Huaibo Song China
Philip Valencia Australia
Grzegorz Cielniak United Kingdom
Hannes Schulz relative to Thomas Hellström Sweden Thomas Hellström's profile →
Citations per field
00.5×10×13.5×
Thomas Hellström · 1×
Citations per year

Countries citing papers authored by Hannes Schulz

Since Specialization
Citations

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

Fields of papers citing papers by Hannes Schulz

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 50 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2015209
2 2015115
3 2017113
4 201864
5 202160
6 201253
7 201353
8 202044
9 201339
10 201631
11
Learning Object-Class Segmentation with Convolutional Neural Networks
201226
12 201625
13 201922
14 201221
15 201720
16 201920
17 201819
18
Investigating Convergence of Restricted Boltzmann Machine Learning
201018
19 201418
20
Multi-Domain Task-Completion Dialog Challenge
201917

About Hannes Schulz

Hannes Schulz is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence, Plant Science, Soil Science and Aerospace Engineering, having authored 50 papers that have together received 1.1k indexed citations. Recurring topics across this work include Advanced Image and Video Retrieval Techniques (8 papers), Topic Modeling (8 papers), Advanced Neural Network Applications (7 papers), Domain Adaptation and Few-Shot Learning (7 papers), Plant nutrient uptake and metabolism (6 papers), Speech and dialogue systems (6 papers), Legume Nitrogen Fixing Symbiosis (5 papers) and Natural Language Processing Techniques (5 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (379 citations), Artificial Intelligence (365 citations), Agronomy and Crop Science (91 citations), Soil Science (81 citations) and Insect Science (94 citations). Hannes Schulz has collaborated with scholars based in Germany, United States and Canada. Frequent co-authors include Sven Behnke, Max Schwarz, Kaheer Suleman, Shikhar Sharma, Layla El Asri, Thorsten Haase, Jürgen Heß, Sascha Kirchner, Jérémie Zumer and Justin Harris. Their work appears in journals such as Neural Networks, Plant and Soil, Neurocomputing, Journal of Cataract & Refractive Surgery and Advanced Robotics.

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.

Explore authors with similar magnitude of impact