Jun Lv

1.2k citations
38 papers · 1.0k · 1 hit paper · h-index 17

Impact in

Papers in

Jun Lv

37 papers receiving 1.0k citations

Jun Lv's Hit Papers

A double-layer attention based adversarial network for partial transfer learning in machinery fault diagnosis 2021 · 204 citations
2040+1+3Years since publication50100150200

Peers

Jun Lv
Comparison fields: 5 of 110
  • Industrial and Manufacturing Engineering 181
  • Statistics, Probability and Uncertainty 82
  • Control and Systems Engineering 258
  • Medical Laboratory Technology 13
  • Mechanical Engineering 276
Replace Chenzhao Li with:
Chenzhao Li United States
Dong Gao China
Huihui Miao China
Shunfeng Cheng United States
Rui He China
Jinsong Yu China
Liang Tang China
Stoyan Stoyanov United Kingdom
Tadahiro Shibutani Japan
Jin Cheng China
Jun Lv relative to Chenzhao Li United States Chenzhao Li's profile →
Citations per field
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Citations per year

Countries citing papers authored by Jun Lv

Since Specialization
Citations

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

Fields of papers citing papers by Jun Lv

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 38 papers — load more, or switch the sort, to bring in the rest.

#Work
1
A double-layer attention based adversarial network for partial transfer learning in machinery fault diagnosis
Hit paper breakdown →
2021204
2 2022109
3 202185
4 201669
5 201369
6 201559
7 202247
8 201245
9 202139
10 201637
11 201433
12 202032
13 201130
14 201026
15 201526
16 202217
17 202316
18 202013
19 201212
20 201911

About Jun Lv

Jun Lv is a scholar working on Electrical and Electronic Engineering, Mechanical Engineering, Industrial and Manufacturing Engineering, Control and Systems Engineering and Computational Mechanics, having authored 38 papers that have together received 1.0k indexed citations. Recurring topics across this work include Manufacturing Process and Optimization (6 papers), Advancements in Battery Materials (6 papers), Advanced Measurement and Metrology Techniques (5 papers), Advanced Battery Materials and Technologies (5 papers), Supercapacitor Materials and Fabrication (5 papers), Advanced machining processes and optimization (4 papers), Machine Fault Diagnosis Techniques (3 papers) and Industrial Vision Systems and Defect Detection (3 papers). The work is most often cited by research in Industrial and Manufacturing Engineering (181 citations), Statistics, Probability and Uncertainty (82 citations), Control and Systems Engineering (258 citations), Medical Laboratory Technology (13 citations) and Mechanical Engineering (276 citations). Jun Lv has collaborated with scholars based in China, Australia and United States. Frequent co-authors include Shichang Du, Yafei Deng, Guilong Li, Delin Huang, Chen Zhao, Chenguang Zhao, Zunxian Yang, Lifeng Xi, Tailiang Guo and Zhanhu Guo. Their work appears in journals such as Journal of Intelligent Manufacturing, Energy, Optics Letters, Scientific Reports and Computers & Industrial Engineering.

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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