Hang Lü

35 papers receiving 297 citations

Peers

Hang Lü
Comparison fields: 5 of 53
  • Hardware and Architecture 61
  • Computer Vision and Pattern Recognition 133
  • Signal Processing 52
  • Artificial Intelligence 90
  • Applied Mathematics 25
Replace Giorgio Vassallo with:
Giorgio Vassallo Italy
Daesung Kwon South Korea
Zheng Huang China
P. P. Deepthi India
Wenbao Han China
H. Schröder Germany
Bryan Usevitch United States
Jiayu Li United States
Tenkasi V. Ramabadran United States
S. Hein United States
Hang Lü relative to Giorgio Vassallo Italy Giorgio Vassallo's profile →
Citations per field
00.5×4.4×
Giorgio Vassallo · 1×
Citations per year

Countries citing papers authored by Hang Lü

Since Specialization
Citations

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

Fields of papers citing papers by Hang Lü

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 40 papers — load more, or switch the sort, to bring in the rest.

#Work
1 202056
2 200552
3 202133
4 201829
5 199328
6 20159
7 20139
8 20237
9 20236
10 20246
11 20216
12 20166
13 20235
14 20175
15 20215
16 20194
17 20194
18 20204
19 20183
20 20223

About Hang Lü

Hang Lü is a scholar working on Computer Vision and Pattern Recognition, Hardware and Architecture, Artificial Intelligence, Electrical and Electronic Engineering and Computer Networks and Communications, having authored 40 papers that have together received 304 indexed citations. Recurring topics across this work include Advanced Neural Network Applications (12 papers), Parallel Computing and Optimization Techniques (9 papers), Interconnection Networks and Systems (6 papers), Adversarial Robustness in Machine Learning (5 papers), Advanced Memory and Neural Computing (4 papers), Cryptography and Data Security (3 papers), Adaptive Control of Nonlinear Systems (3 papers) and Domain Adaptation and Few-Shot Learning (3 papers). The work is most often cited by research in Hardware and Architecture (61 citations), Computer Vision and Pattern Recognition (133 citations), Signal Processing (52 citations), Artificial Intelligence (90 citations) and Applied Mathematics (25 citations). Hang Lü has collaborated with scholars based in China, United States and Hong Kong. Frequent co-authors include Xiaowei Li, Ning Lin, John S. Todhunter, Liang Chang, Guihai Yan, Feng Pan, K.P. Lim, Susanto Rahardja, Z.G. Li and Xian Lin. Their work appears in journals such as IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems, IEEE Transactions on Very Large Scale Integration (VLSI) Systems, Science China Information Sciences, International Journal of Systems Science and Journal of Visual Communication and Image Representation.

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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