S. Y. Lu

589 citations
20 papers · 327 · h-index 9

Impact in

Papers in

S. Y. Lu

17 papers receiving 308 citations

Peers

S. Y. Lu
Comparison fields: 5 of 67
  • Computer Graphics and Computer-Aided Design 36
  • Computer Vision and Pattern Recognition 159
  • Artificial Intelligence 134
  • Media Technology 36
  • Management Science and Operations Research 25
Replace Piero Zamperoni with:
Piero Zamperoni Germany
Soumya Dutta United States
Song-Chun Zhu United States
Cong Lin China
Nina S. T. Hirata Brazil
Jianwei Li China
Andrew D. J. Cross United Kingdom
P S P Wang Mexico
Devansh Arpit Canada
S. Y. Lu relative to Piero Zamperoni Germany Piero Zamperoni's profile →
Citations per field
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Piero Zamperoni · 1×
Citations per year

Countries citing papers authored by S. Y. Lu

Since Specialization
Citations

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

Fields of papers citing papers by S. Y. Lu

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by S. Y. Lu. 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 S. Y. Lu. The network helps show where S. Y. Lu may publish in the future.

Co-authors

The 24 scholars most cited alongside S. Y. Lu, 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 S. Y. Lu Line = papers co-authored together S. Y. Lu links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown
#Work
1 197885
2 198839
3 199133
4 198433
5 197930
6 197823
7 200214
8
A set-theoretic framework for the processing of uncertain knowledge
198413
9 19909
10 19768
11 19898
12 19908
13 20027
14 20236
15 20246
16 20024
17
Error-Correcting Syntax Analysis for Tree Languages.
19761
18 20250
19 20250
20 20030

About S. Y. Lu

S. Y. Lu is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition, Computer Networks and Communications, Signal Processing and Hardware and Architecture, having authored 20 papers that have together received 327 indexed citations. Recurring topics across this work include Algorithms and Data Compression (4 papers), Image Retrieval and Classification Techniques (3 papers), Multi-Criteria Decision Making (2 papers), Network Packet Processing and Optimization (2 papers), Data Management and Algorithms (2 papers), Bayesian Modeling and Causal Inference (2 papers), Neural Networks and Applications (2 papers) and Image Processing and 3D Reconstruction (2 papers). The work is most often cited by research in Computer Graphics and Computer-Aided Design (36 citations), Computer Vision and Pattern Recognition (159 citations), Artificial Intelligence (134 citations), Media Technology (36 citations) and Management Science and Operations Research (25 citations). S. Y. Lu has collaborated with scholars based in United States, China and Taiwan. Frequent co-authors include K. S. Fu, H.E. Stephanou, J. Patrick Fitch, Farid Dowla, Dennis M. Goodman, Erik M. J. Johansson, J. E. Hernández, James G. Berryman, Gregory A. Clark and R. J. Sherwood. Their work appears in journals such as IEEE Transactions on Pattern Analysis and Machine Intelligence, IEEE Access, International Journal of Imaging Systems and Technology, IEEE Transactions on Information Forensics and Security and IEEE Transactions on Geoscience and Remote Sensing.

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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