Jan Ernst
Impact in
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- Video Analysis and Summarization
- Advanced Image and Video Retrieval Techniques
- Advanced Neural Network Applications
- Multimodal Machine Learning Applications
- Human Pose and Action Recognition
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- Music and Audio Processing
Papers in ⓘ
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- Advanced Image and Video Retrieval Techniques 3
- Advanced Neural Network Applications 2
- Video Surveillance and Tracking Methods 1
- Multimodal Machine Learning Applications 1
- Image Retrieval and Classification Techniques 1
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- Domain Adaptation and Few-Shot Learning 1
- Co-authors
- Ziyan Wu (2 shared papers)Amit K. Roy–Chowdhury (1 shared paper)Abir Das (1 shared paper)Rameswar Panda (1 shared paper)Kuan–Chuan Peng (1 shared paper)Yun Fu (1 shared paper)Kunpeng Li (1 shared paper)Shanhui Sun (1 shared paper)
- Journals
- IEEE Transactions on Pattern Analysis and Machine Intelligence (1 paper)1996 IEEE Nuclear Science Symposium. Conference Record (1 paper)arXiv (Cornell University) (1 paper)
- Partner nations
- United StatesGermany
In The Last Decade
Jan Ernst
6 papers receiving 135 citations
Peers
Comparison fields: 5 of 43
- Computer Vision and Pattern Recognition 100
- Signal Processing 38
- Health Informatics 2
- Artificial Intelligence 35
- Radiology, Nuclear Medicine and Imaging 15
Countries citing papers authored by Jan Ernst
This map shows the geographic impact of Jan Ernst'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 Jan Ernst with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Jan Ernst more than expected).
Fields of papers citing papers by Jan Ernst
This network shows the impact of papers produced by Jan Ernst. 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 Jan Ernst. The network helps show where Jan Ernst may publish in the future.
Co-authors
The 19 scholars most cited alongside Jan Ernst, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | 2017 | 66 | |
| 2 | 2019 | 43 | |
| 3 | 2014 | 19 | |
| 4 | 2012 | 5 | |
| 5 | 2021 | 4 | |
| 6 | 2002 | 1 |
About Jan Ernst
Jan Ernst is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence, Computer Networks and Communications, Hardware and Architecture and Aerospace Engineering, having authored 6 papers that have together received 138 indexed citations. Recurring topics across this work include Advanced Image and Video Retrieval Techniques (3 papers), Advanced Neural Network Applications (2 papers), Domain Adaptation and Few-Shot Learning (1 paper), Video Surveillance and Tracking Methods (1 paper), Robotics and Sensor-Based Localization (1 paper), Multimodal Machine Learning Applications (1 paper), Image Retrieval and Classification Techniques (1 paper) and Advancements in PLL and VCO Technologies (1 paper). The work is most often cited by research in Computer Vision and Pattern Recognition (100 citations), Signal Processing (38 citations), Health Informatics (2 citations), Artificial Intelligence (35 citations) and Radiology, Nuclear Medicine and Imaging (15 citations). Jan Ernst has collaborated with scholars based in United States and Germany. Frequent co-authors include Ziyan Wu, Amit K. Roy–Chowdhury, Abir Das, Rameswar Panda, Kuan–Chuan Peng, Yun Fu, Kunpeng Li, Shanhui Sun, Joachim Bamberger and Terrence Chen. Their work appears in journals such as IEEE Transactions on Pattern Analysis and Machine Intelligence, 1996 IEEE Nuclear Science Symposium. Conference Record and arXiv (Cornell University).
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.