Patrick Helber

2.5k total citations · 1 hit paper
22 papers, 1.3k citations indexed

About

Patrick Helber is a scholar working on Media Technology, Ecology and Artificial Intelligence. According to data from OpenAlex, Patrick Helber has authored 22 papers receiving a total of 1.3k indexed citations (citations by other indexed papers that have themselves been cited), including 8 papers in Media Technology, 7 papers in Ecology and 7 papers in Artificial Intelligence. Recurrent topics in Patrick Helber's work include Remote-Sensing Image Classification (8 papers), Remote Sensing in Agriculture (7 papers) and Remote Sensing and Land Use (4 papers). Patrick Helber is often cited by papers focused on Remote-Sensing Image Classification (8 papers), Remote Sensing in Agriculture (7 papers) and Remote Sensing and Land Use (4 papers). Patrick Helber collaborates with scholars based in Germany, Netherlands and Switzerland. Patrick Helber's co-authors include Benjamin Bischke, Damian Borth, Andreas Dengel, J.J. van Hees, Zhengyu Zhao, Jens de Bruijn, Birgit Kleinschmit, Christian Schulz, Michael Förster and Begüm Demir and has published in prestigious journals such as Remote Sensing of Environment, IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing and Earth system science data.

In The Last Decade

Patrick Helber

20 papers receiving 1.3k citations

Hit Papers

EuroSAT: A Novel Dataset and Deep Learning Benchmark for ... 2019 2026 2021 2023 2019 250 500 750
What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

  1. EuroSAT: A Novel Dataset and Deep Learning Benchmark for Land Use and Land Cover Classification
    2019 960 citations Patrick Helber, Benjamin Bischke et al. profile →

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Patrick Helber Germany 10 510 507 493 251 183 22 1.3k
Benjamin Bischke Germany 12 561 1.1× 546 1.1× 533 1.1× 268 1.1× 205 1.1× 27 1.5k
Jingwen Hu China 13 525 1.0× 343 0.7× 636 1.3× 234 0.9× 306 1.7× 32 1.5k
Grant J. Scott United States 16 545 1.1× 248 0.5× 566 1.1× 213 0.8× 186 1.0× 102 1.3k
Consuelo Gonzalo‐Martín Spain 20 331 0.6× 189 0.4× 525 1.1× 233 0.9× 139 0.8× 94 1.1k
Otávio A. B. Penatti Brazil 15 1.1k 2.2× 422 0.8× 1.1k 2.2× 286 1.1× 409 2.2× 42 2.1k
Biplab Banerjee India 20 669 1.3× 421 0.8× 660 1.3× 125 0.5× 231 1.3× 123 1.3k
Aizhu Zhang China 22 349 0.7× 290 0.6× 646 1.3× 155 0.6× 364 2.0× 64 1.2k
Xingxing Xie China 15 1.2k 2.4× 321 0.6× 964 2.0× 145 0.6× 265 1.4× 21 2.0k
Fan Hu China 12 771 1.5× 189 0.4× 977 2.0× 239 1.0× 389 2.1× 20 1.4k
Valero Laparra Spain 19 532 1.0× 234 0.5× 360 0.7× 336 1.3× 151 0.8× 73 1.4k

Countries citing papers authored by Patrick Helber

Since Specialization
Citations

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

Fields of papers citing papers by Patrick Helber

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Patrick Helber

This figure shows the co-authorship network connecting the top 25 collaborators of Patrick Helber. A scholar is included among the top collaborators of Patrick Helber based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Patrick Helber. Patrick Helber is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
1.
2.
Mena, Francisco, Deepak Pathak, Patrick Helber, et al.. (2024). Adaptive fusion of multi-modal remote sensing data for optimal sub-field crop yield prediction. Remote Sensing of Environment. 318. 114547–114547. 21 indexed citations
3.
Schulz, Christian, Patrick Helber, Benjamin Bischke, et al.. (2023). TreeSatAI Benchmark Archive : a multi-sensor, multi-label dataset for tree species classification in remote sensing. Earth system science data. 15(2). 681–695. 36 indexed citations
4.
Helber, Patrick, Benjamin Bischke, Deepak Pathak, et al.. (2023). Crop Yield Prediction: An Operational Approach to Crop Yield Modeling on Field and Subfield Level with Machine Learning Models. 2763–2766. 9 indexed citations
5.
Helber, Patrick, Benjamin Bischke, Francisco Mena, et al.. (2023). Feature Attribution Methods for Multivariate Time-Series Explainability in Remote Sensing. 5014–5017. 5 indexed citations
6.
Pathak, Deepak, Marcela Charfuelàn, Patrick Helber, et al.. (2023). Influence of Data Cleaning Techniques on Sub-Field Yield Predictions. 4852–4855. 6 indexed citations
7.
Pathak, Deepak, Francisco Mena, Patrick Helber, et al.. (2023). Predicting Crop Yield with Machine Learning: An Extensive Analysis of Input Modalities and Models on a Field and Sub-Field Level. 2767–2770. 5 indexed citations
8.
Bischke, Benjamin, Patrick Helber, Çağlar Şenaras, et al.. (2022). Rapidai4Eo: Mono-and Multi-Temporal Deep Learning Models for Updating the Corine land Cover Product. IGARSS 2022 - 2022 IEEE International Geoscience and Remote Sensing Symposium. 2247–2250. 3 indexed citations
9.
Bischke, Benjamin, et al.. (2019). Flood Severity Estimation from Online News Images and Multi-Temporal Satellite Images Using Deep Neural Networks.. MediaEval. 1 indexed citations
10.
Helber, Patrick, Benjamin Bischke, J.J. van Hees, & Andreas Dengel. (2019). Towards a Sentinel-2 Based Human Settlement Layer. 5936–5939. 7 indexed citations
11.
Bischke, Benjamin, Patrick Helber, J.J. van Hees, & Andreas Dengel. (2019). Location-Specific Embedding Learning for the Semantic Segmentation of Building Footprints on a Global Scale. 2 indexed citations
12.
Helber, Patrick, Benjamin Bischke, Qiushi Guo, J.J. van Hees, & Andreas Dengel. (2019). Multi-Scale Machine Learning for the Classification of Building Property Values. 4873–4876. 4 indexed citations
13.
Bischke, Benjamin, Patrick Helber, & Andreas Dengel. (2018). Global-Local Feature Fusion for Image Classification of Flood Affected Roads from Social Multimedia.. MediaEval. 4 indexed citations
14.
15.
Bischke, Benjamin, Patrick Helber, Zhengyu Zhao, Jens de Bruijn, & Damian Borth. (2018). The Multimedia Satellite Task at MediaEval 2018: Emergency Response for Flooding Events. VU Research Portal. 1–3. 24 indexed citations
16.
Bischke, Benjamin, Patrick Helber, Damian Borth, & Andreas Dengel. (2018). Segmentation of Imbalanced Classes in Satellite Imagery using Adaptive Uncertainty Weighted Class Loss. 6191–6194. 17 indexed citations
17.
Bischke, Benjamin, et al.. (2017). The Multimedia Satellite Task at MediaEval 2017. Alexandria (UniSG) (University of St.Gallen). 7 indexed citations
18.
Bischke, Benjamin, et al.. (2017). Detection of Flooding Events in Social Multimedia and Satellite Imagery using Deep Neural Networks.. MediaEval. 39 indexed citations
19.
Bischke, Benjamin, et al.. (2017). The Multimedia Satellite Task at MediaEval 2017. MediaEval. 9 indexed citations
20.

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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