Benjamin Kellenberger

2.7k citations
32 papers · 1.6k · 1 hit paper · h-index 14

Impact in

Papers in

Benjamin Kellenberger

29 papers receiving 1.6k citations

Benjamin Kellenberger's Hit Papers

Perspectives in machine learning for wildlife conservation 2022 · 417 citations
4170+1+2Years since publication100200300400

Peers

Benjamin Kellenberger
Comparison fields: 5 of 115
  • Ecological Modeling 219
  • Media Technology 254
  • Computer Vision and Pattern Recognition 581
  • Developmental Biology 57
  • Ecology 471
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Grant Van Horn United States
Tilo Burghardt United Kingdom
Renato J. Cintra Brazil
Tsung‐Yu Lin United States
Steve Branson United States
Alexis Joly France
Volker Steinhage Germany
Silvia Zuffi Italy
Wesley Nunes Gonçalves Brazil
Zhihai He United States
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Citations per year

Countries citing papers authored by Benjamin Kellenberger

Since Specialization
Citations

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

Fields of papers citing papers by Benjamin Kellenberger

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 32 papers — load more, or switch the sort, to bring in the rest.

#Work
1
Perspectives in machine learning for wildlife conservation
Hit paper breakdown →
2022417
2 2018244
3 2018241
4 2018231
5 2019103
6 201782
7 202060
8 202141
9 202034
10 202230
11 201921
12 202217
13 202115
14 202115
15 202012
16 20249
17 20238
18 20198
19 20167
20 20187

About Benjamin Kellenberger

Benjamin Kellenberger is a scholar working on Ecology, Computer Vision and Pattern Recognition, Ecological Modeling, Artificial Intelligence and Molecular Biology, having authored 32 papers that have together received 1.6k indexed citations. Recurring topics across this work include Species Distribution and Climate Change (10 papers), Advanced Image and Video Retrieval Techniques (8 papers), Domain Adaptation and Few-Shot Learning (7 papers), Wildlife Ecology and Conservation (6 papers), Advanced Neural Network Applications (6 papers), Robotics and Sensor-Based Localization (4 papers), Remote-Sensing Image Classification (4 papers) and Remote Sensing in Agriculture (3 papers). The work is most often cited by research in Ecological Modeling (219 citations), Media Technology (254 citations), Computer Vision and Pattern Recognition (581 citations), Developmental Biology (57 citations) and Ecology (471 citations). Benjamin Kellenberger has collaborated with scholars based in Switzerland, Netherlands and United States. Frequent co-authors include Devis Tuia, Diego Marcos, Michele Volpi, Nicolas Courty, Rémi Flamary, Bharath Bhushan Damodaran, Sylvain Lobry, Iain D. Couzin, Blair R. Costelloe and Frank van Langevelde. Their work appears in journals such as Remote Sensing of Environment, Methods in Ecology and Evolution, Scientific Reports, Ecological Informatics and IEEE Transactions on Geoscience and Remote Sensing.

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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