Nanyi Fei

23 total papers · 509 total citations
9 papers, 295 citations indexed

About

Nanyi Fei is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence and Neurology. According to data from OpenAlex, Nanyi Fei has authored 9 papers receiving a total of 295 indexed citations (citations by other indexed papers that have themselves been cited), including 9 papers in Computer Vision and Pattern Recognition, 4 papers in Artificial Intelligence and 1 paper in Neurology. Recurrent topics in Nanyi Fei's work include Domain Adaptation and Few-Shot Learning (4 papers), Multimodal Machine Learning Applications (4 papers) and Advanced Image and Video Retrieval Techniques (3 papers). Nanyi Fei is often cited by papers focused on Domain Adaptation and Few-Shot Learning (4 papers), Multimodal Machine Learning Applications (4 papers) and Advanced Image and Video Retrieval Techniques (3 papers). Nanyi Fei collaborates with scholars based in China, Hong Kong and United Kingdom. Nanyi Fei's co-authors include Tao Xiang, Haoyu Lu, Zhiwu Lu, Yuqi Huo, Ji-Rong Wen, Yizhao Gao, Guoxing Yang, Zhiwu Lu, Hao Sun and Ruihua Song and has published in prestigious journals such as Nature Communications, 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) and Neural Information Processing Systems.

In The Last Decade

Nanyi Fei

6 papers receiving 288 citations

Hit Papers

Towards artificial genera... 2022 2026 2023 2024 2022 50 100 150

Author Peers

Peers are selected by citation overlap in the author's most active subfields. citations · hero ref

Author Last Decade Papers Cites
Nanyi Fei 153 138 31 22 14 9 295
Haoyu Lu 122 0.8× 113 0.8× 27 0.9× 22 1.0× 19 1.4× 22 283
A. Lamas 150 1.0× 151 1.1× 16 0.5× 13 0.6× 15 1.1× 10 302
David Münch 114 0.7× 87 0.6× 24 0.8× 9 0.4× 13 0.9× 10 286
Rahul Nair 97 0.6× 182 1.3× 23 0.7× 22 1.0× 8 0.6× 13 347
Yuxuan Luo 133 0.9× 78 0.6× 28 0.9× 6 0.3× 12 0.9× 12 247
Neha Sharma 66 0.4× 83 0.6× 28 0.9× 11 0.5× 22 1.6× 12 293
Beddhu Murali 100 0.7× 176 1.3× 32 1.0× 12 0.5× 12 0.9× 9 320
Mohammad Ashraf Ottom 115 0.8× 94 0.7× 44 1.4× 10 0.5× 14 1.0× 17 354
Ruihua Song 141 0.9× 84 0.6× 20 0.6× 23 1.0× 9 0.6× 20 308
Eman Alajrami 156 1.0× 70 0.5× 95 3.1× 17 0.8× 15 1.1× 11 333

Countries citing papers authored by Nanyi Fei

Since Specialization
Citations

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

Fields of papers citing papers by Nanyi Fei

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Nanyi Fei

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

All Works

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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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