Lu Jin

714 citations
20 papers · 531 indexed · h-index 10

Lu Jin

19 papers receiving 515 citations

Peers

Lu Jin
Comparison fields: 5 of 61
  • Computer Vision and Pattern Recognition 379
  • Management Science and Operations Research 87
  • Artificial Intelligence 156
  • Media Technology 32
  • Statistics and Probability 30
Replace Hanuman Verma with:
Hanuman Verma India
Zhou Liu China
Carl Frélicot France
Yanpeng Qu China
Hubert Emptoz France
Justin Domke United States
Hongseok Namkoong United States
Sheng Feng China
Nati Srebro United States
S. Ramathilagam India
Lu Jin relative to Hanuman Verma India Hanuman Verma's profile →
Citations per field
00.5×1.5×2.1×
Hanuman Verma · 1×
Citations per year

Countries citing papers authored by Lu Jin

Since Specialization
Citations

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

Fields of papers citing papers by Lu Jin

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network

The 19 scholars most cited alongside Lu Jin, 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 Lu Jin Line = papers co-authored together Lu Jin links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown
#Work
1 20242
2 20243
3 202312
4 20234
5 202322
6 20215
7 202080
8 202022
9 20200
10 20192
11 20195
12 201865
13 201881
14 20183
15 201734
16 20154
17 201548
18 201434
19 20132
20 2011103

About Lu Jin

Lu Jin is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence, Statistics and Probability, Management Science and Operations Research and Aerospace Engineering, having authored 20 papers that have together received 531 indexed citations. Recurring topics across this work include Advanced Image and Video Retrieval Techniques (17 papers), Image Retrieval and Classification Techniques (8 papers), Multimodal Machine Learning Applications (8 papers), Video Surveillance and Tracking Methods (8 papers), Advanced Neural Network Applications (6 papers), Domain Adaptation and Few-Shot Learning (4 papers), Human Pose and Action Recognition (2 papers) and Fuzzy Systems and Optimization (1 paper). The work is most often cited by research in Computer Vision and Pattern Recognition (379 citations), Management Science and Operations Research (87 citations), Artificial Intelligence (156 citations), Media Technology (32 citations) and Statistics and Probability (30 citations). Lu Jin has collaborated with scholars based in China and United States. Frequent co-authors include Jinhui Tang, Zechao Li, Abraham Kandel, Dan E. Tamir, Guo-Jun Qi, Shenghua Gao, Kai Li, Xiangbo Shu, Kai Li and Fu Xiao. Their work appears in journals such as IEEE Transactions on Multimedia, IEEE Transactions on Neural Networks and Learning Systems, IEEE Transactions on Image Processing, IEEE Transactions on Pattern Analysis and Machine Intelligence 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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