Lele Fu

722 citations
27 papers · 464 · 1 hit paper · h-index 10

Impact in

Papers in

Lele Fu

24 papers receiving 461 citations

Lele Fu's Hit Papers

Learnable graph convolutional network and feature fusion for multi-view learning 2023 · 110 citations
1100+1+2Years since publication255075100

Peers

Lele Fu
Comparison fields: 5 of 61
  • Computational Mathematics 46
  • Computer Vision and Pattern Recognition 290
  • Urban Studies 52
  • Artificial Intelligence 271
  • Media Technology 45
Replace Xinzhong Zhu with:
Xinzhong Zhu China
Danyang Wu China
Shide Du China
Lai Tian China
Chong Peng United States
Bassoma Diallo China
Gui-Fu Lu China
Gui‐Fu Lu China
Lele Fu relative to Xinzhong Zhu China Xinzhong Zhu's profile →
Citations per field
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Xinzhong Zhu · 1×
Citations per year

Countries citing papers authored by Lele Fu

Since Specialization
Citations

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

Fields of papers citing papers by Lele Fu

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 27 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2020132
2
Learnable graph convolutional network and feature fusion for multi-view learning
Hit paper breakdown →
2023110
3 202241
4 202240
5 202220
6 202219
7 202216
8 202112
9 20239
10 20239
11 20229
12 20247
13 20227
14 20217
15 20246
16 20245
17 20243
18 20223
19 20242
20 20252

About Lele Fu

Lele Fu is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition, Computational Mathematics, Computational Mechanics and Media Technology, having authored 27 papers that have together received 464 indexed citations. Recurring topics across this work include Face and Expression Recognition (11 papers), Tensor decomposition and applications (8 papers), Video Surveillance and Tracking Methods (7 papers), Privacy-Preserving Technologies in Data (5 papers), Advanced Graph Neural Networks (5 papers), Sparse and Compressive Sensing Techniques (5 papers), Advanced Clustering Algorithms Research (4 papers) and Image Retrieval and Classification Techniques (4 papers). The work is most often cited by research in Computational Mathematics (46 citations), Computer Vision and Pattern Recognition (290 citations), Urban Studies (52 citations), Artificial Intelligence (271 citations) and Media Technology (45 citations). Lele Fu has collaborated with scholars based in China, Hong Kong and Macao. Frequent co-authors include Shiping Wang, Athanasios V. Vasilakos, Pengfei Lin, Zhaoliang Chen, Chuan Chen, Wenzhong Guo, Claudia Plant, Jing‐Hua Yang, Chuanfu Zhang and Zibin Zheng. Their work appears in journals such as ACM Transactions on Knowledge Discovery from Data, Neurocomputing, Information Sciences, Neural Networks and IEEE Transactions on Multimedia.

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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