Ranjie Duan

735 citations
7 papers · 405 indexed · h-index 5
Topics
Adversarial Robustness in Machine Learning (6 papers)Anomaly Detection Techniques and Applications (3 papers)Advanced Neural Network Applications (2 papers)
Journals
Pattern Recognition LettersIEEE Transactions on Information Forensics and Security2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)

In The Last Decade

Ranjie Duan

6 papers receiving 397 citations

Peers

Ranjie Duan
Comparison fields: 5 of 57
  • Artificial Intelligence 312
  • Computer Vision and Pattern Recognition 155
  • Signal Processing 72
  • Hardware and Architecture 50
  • Electrical and Electronic Engineering 47
Replace Wiebe Van Ranst with:
Wiebe Van Ranst Belgium
Donghua Wang China
Qidong Huang China
Manaar Alam India
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Kaichen Yang United States
Philipp Gysel United States
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Ranjie Duan relative to Wiebe Van Ranst Belgium Wiebe Van Ranst's profile →
Citations per field
00.5×1.5×1.8×
Wiebe Van Ranst · 1×
Citations per year

Countries citing papers authored by Ranjie Duan

Since Specialization
Citations

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

Fields of papers citing papers by Ranjie Duan

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Ranjie Duan

This figure shows the co-authorship network connecting the top 25 collaborators of Ranjie Duan. A scholar is included among the top collaborators of Ranjie Duan 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 Ranjie Duan. Ranjie Duan is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

7 of 7 papers shown
#WorkIndexed citations
1 0
2 6
3 2
4 117
5 61
6 86
7 133

About Ranjie Duan

Ranjie Duan is a scholar working on Hardware and Architecture, Instrumentation and Artificial Intelligence, having authored 7 papers that have together received 405 indexed citations. Recurring topics across this work include Adversarial Robustness in Machine Learning (6 papers), Anomaly Detection Techniques and Applications (3 papers) and Advanced Neural Network Applications (2 papers). The work is most often cited by research in Artificial Intelligence (312 citations), Computer Vision and Pattern Recognition (155 citations) and Hardware and Architecture (50 citations). Ranjie Duan has collaborated with scholars based in China, Australia and United States. Frequent co-authors include A. K. Qin, Yun Yang, Yuan He, Xiaofeng Mao, Yuefeng Chen, Yisen Wang, Xingjun Ma, James Bailey, Hui Xue and Xiaodan Li. Their work appears in journals such as Pattern Recognition Letters, IEEE Transactions on Information Forensics and Security and 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR).

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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