Michael Kopp

12 papers receiving 281 citations

Hit Papers

Landslide4Sense: Reference Benchmark Data and Deep Learning Models for Landslide Detection 2022 · 115 citations
1150+1+2Years since publication255075100

Peers

Michael Kopp
Comparison fields: 5 of 77
  • Management, Monitoring, Policy and Law 94
  • Media Technology 37
  • Artificial Intelligence 105
  • Computer Vision and Pattern Recognition 61
  • Global and Planetary Change 58
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T. Hemalatha India
Khwairakpam Amitab India
Liang-Hao Huang China
S. Prabu India
Pengyuan Lv China
Wen-Yew Liang Taiwan
Qin Dai China
Zhiyuan Zeng China
André Mora Portugal
Pei‐Jun Lee Taiwan
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Citations per field
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Countries citing papers authored by Michael Kopp

Since Specialization
Citations

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

Fields of papers citing papers by Michael Kopp

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

14 of 14 papers shown
#Work
1
Landslide4Sense: Reference Benchmark Data and Deep Learning Models for Landslide Detection
Hit paper breakdown →
2022115
2
Hopfield Networks is All You Need
202177
3 202336
4 202332
5 20227
6 20217
7 20235
8 20215
9 20243
10
Traffic4cast at NeurIPS 2020 - yet more on the unreasonable effectiveness of gridded geo-spatial processes
20213
11 20041
12 20241
13
Traffic4cast at NeurIPS 2020 ? yet more on theunreasonable effectiveness of gridded geo-spatial processes.
20201
14
The surprising efficiency of framing geo-spatial time series forecasting as a video prediction task - Insights from the IARAI Traffic4cast Competition at NeurIPS 2019.
20190

About Michael Kopp

Michael Kopp is a scholar working on Artificial Intelligence, Molecular Biology, Computer Vision and Pattern Recognition, Media Technology and Atmospheric Science, having authored 14 papers that have together received 293 indexed citations. Recurring topics across this work include Flood Risk Assessment and Management (2 papers), Advanced Chemical Sensor Technologies (1 paper), Complex Network Analysis Techniques (1 paper), Remote-Sensing Image Classification (1 paper), Time Series Analysis and Forecasting (1 paper), Automated Road and Building Extraction (1 paper), Remote Sensing and Land Use (1 paper) and Multimodal Machine Learning Applications (1 paper). The work is most often cited by research in Management, Monitoring, Policy and Law (94 citations), Media Technology (37 citations), Artificial Intelligence (105 citations), Computer Vision and Pattern Recognition (61 citations) and Global and Planetary Change (58 citations). Michael Kopp has collaborated with scholars based in Austria, Germany and Spain. Frequent co-authors include Pedram Ghamisi, David P. Kreil, Yonghao Xu, Omid Ghorbanzadeh, Sepp Hochreiter, Michael Widrich, Weikang Yu, Lukas Gruber, Günter Klambauer and Johannes M. Lehner. Their work appears in journals such as IEEE Transactions on Geoscience and Remote Sensing, IEEE Transactions on Intelligent Transportation Systems, IEEE Transactions on Image Processing, Nature Machine Intelligence and Archiv der Mathematik.

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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