Yan Lu

4.8k citations
135 papers · 2.8k indexed · 1 hit paper · h-index 25

Yan Lu

122 papers receiving 2.7k citations

Hit Papers

Relational Knowledge Distillation8942019202620212023250500750

Peers

Yan Lu
Comparison fields: 5 of 130
  • Computer Vision and Pattern Recognition 2.1k
  • Signal Processing 689
  • Artificial Intelligence 763
  • Media Technology 198
  • Computer Graphics and Computer-Aided Design 59
Replace Zhifeng Li with:
Zhifeng Li China
Baoyuan Wu China
Shao‐Yi Chien Taiwan
Ming–Ting Sun United States
Zhijun Fang China
Rogério Feris United States
Ivan V. Bajić Canada
Feng Dai China
Shang‐Hong Lai Taiwan
Zuxuan Wu China
Yan Lu relative to Zhifeng Li China Zhifeng Li's profile →
Citations per field
00.5×
Zhifeng Li · 1×
Citations per year

Countries citing papers authored by Yan Lu

Since Specialization
Citations

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

Fields of papers citing papers by Yan Lu

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network

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

All Works

20 of 20 papers shown
#Work
1 20250
2 20250
3 202425
4 20240
5 20240
6 20240
7 20240
8 20238
9 20231
10 20227
11 202213
12 20217
13 20196
14 20188
15 201415
16 20148
17
The Application of Harris Corner Detection in Color Imagine
20090
18 20057
19 20044
20 20046

About Yan Lu

Yan Lu is a scholar working on Signal Processing, Computer Vision and Pattern Recognition and Hardware and Architecture, having authored 135 papers that have together received 2.8k indexed citations. Recurring topics across this work include Video Coding and Compression Technologies (45 papers), Advanced Vision and Imaging (34 papers), Advanced Data Compression Techniques (31 papers), Image and Video Quality Assessment (15 papers), Advanced Image and Video Retrieval Techniques (15 papers), Speech and Audio Processing (13 papers), Advanced Image Processing Techniques (13 papers) and Cloud Computing and Remote Desktop Technologies (12 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (2.1k citations), Signal Processing (689 citations) and Artificial Intelligence (763 citations). Yan Lu has collaborated with scholars based in China, United States and Hong Kong. Frequent co-authors include Minsu Cho, Shipeng Li, Jinglu Wang, Xun Guo, Huifeng Shen, Zengyi Qin, Bin Li, Jiahao Li, Feng Wu and Feng Wu. Their work appears in journals such as IEEE Transactions on Circuits and Systems for Video Technology, ACM Transactions on Multimedia Computing Communications and Applications, IEEE Transactions on Multimedia, Signal Processing Image Communication and IEEE Signal Processing Letters.

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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