Danlu Chen
Impact in
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- Advanced Neural Network Applications
- Advanced Image and Video Retrieval Techniques
- Multimodal Machine Learning Applications
- Video Surveillance and Tracking Methods
- Human Pose and Action Recognition
- Artificial Intelligence top 10%
- Domain Adaptation and Few-Shot Learning
- Adversarial Robustness in Machine Learning
- Anomaly Detection Techniques and Applications
Papers in
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- Advanced Neural Network Applications 2
- Currency Recognition and Detection 1
- Digital Imaging for Blood Diseases 1
- Image Processing and 3D Reconstruction 1
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- Domain Adaptation and Few-Shot Learning 2
- Machine Learning and Data Classification 1
- Co-authors
- Tianhong Li (2 shared papers)Felix Wu (2 shared papers)Kilian Q. Weinberger (2 shared papers)Laurens van der Maaten (2 shared papers)Gao Huang (2 shared papers)Taylor Berg-Kirkpatrick (1 shared paper)
- Journals
- DOAJ (DOAJ: Directory of Open Access Journals) (1 paper)arXiv (Cornell University) (2 papers)
- Partner nations
- United StatesNetherlands
In The Last Decade
Danlu Chen
2 papers receiving 184 citations
Peers
Comparison fields: 5 of 54
- Computer Vision and Pattern Recognition 139
- Artificial Intelligence 101
- Media Technology 14
- Neurology 8
- Tourism, Leisure and Hospitality Management 1
Countries citing papers authored by Danlu Chen
This map shows the geographic impact of Danlu Chen'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 Danlu Chen with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Danlu Chen more than expected).
Fields of papers citing papers by Danlu Chen
This network shows the impact of papers produced by Danlu Chen. 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 Danlu Chen. The network helps show where Danlu Chen may publish in the future.
Co-authors
The 6 scholars most cited alongside Danlu Chen, 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 | 121 | |
| 2 | Multi-Scale Dense Convolutional Networks for Efficient Prediction. | 2017 | 69 |
| 3 | 2023 | 0 |
About Danlu Chen
Danlu Chen is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence, Signal Processing, Infectious Diseases and Organic Chemistry, having authored 3 papers that have together received 190 indexed citations. Recurring topics across this work include Advanced Neural Network Applications (2 papers), Domain Adaptation and Few-Shot Learning (2 papers), Machine Learning and Data Classification (1 paper), Time Series Analysis and Forecasting (1 paper), Currency Recognition and Detection (1 paper), Digital Imaging for Blood Diseases (1 paper) and Image Processing and 3D Reconstruction (1 paper). The work is most often cited by research in Computer Vision and Pattern Recognition (139 citations), Artificial Intelligence (101 citations), Media Technology (14 citations), Neurology (8 citations) and Tourism, Leisure and Hospitality Management (1 citation). Danlu Chen has collaborated with scholars based in United States and Netherlands. Frequent co-authors include Tianhong Li, Felix Wu, Kilian Q. Weinberger, Laurens van der Maaten, Gao Huang and Taylor Berg-Kirkpatrick. Their work appears in journals such as DOAJ (DOAJ: Directory of Open Access Journals) 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.