Jun Liu

8.2k citations
361 papers · 5.8k · 1 hit paper · h-index 42

Impact in

Papers in

Jun Liu

324 papers receiving 5.6k citations

Jun Liu's Hit Papers

Multichannel adaptive signal detection: basic theory and literature review 2022 · 188 citations
1880+1+2Years since publication50100150

Peers

Jun Liu
Comparison fields: 5 of 155
  • Aerospace Engineering 3.5k
  • Signal Processing 1.3k
  • Computational Mathematics 32
  • Media Technology 427
  • Oceanography 418
Replace Wei Liu with:
Wei Liu China
Andrew Graham Dempster Australia
Bo Chen China
Zhi Jun Ding United States
David J. Salmond United Kingdom
Wei Ren Chen China
David Suter Australia
Yongming Huang China
Gang Li China
Jie Wang China
Jun Liu relative to Wei Liu China Wei Liu's profile →
Citations per field
00.5×1.5×2.1×
Wei Liu · 1×
Citations per year

Countries citing papers authored by Jun Liu

Since Specialization
Citations

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

Fields of papers citing papers by Jun Liu

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 361 papers — load more, or switch the sort, to bring in the rest.

#Work
1
Multichannel adaptive signal detection: basic theory and literature review
Hit paper breakdown →
2022188
2 2014180
3 2021129
4 2014100
5 199995
6 201392
7 201787
8 202382
9 201979
10 200677
11 201576
12 201474
13 200873
14 201573
15 201572
16 200472
17 201369
18 202168
19 201568
20 200367

About Jun Liu

Jun Liu is a scholar working on Aerospace Engineering, Signal Processing, Media Technology, Computer Networks and Communications and Computer Vision and Pattern Recognition, having authored 361 papers that have together received 5.8k indexed citations. Recurring topics across this work include Radar Systems and Signal Processing (142 papers), Advanced SAR Imaging Techniques (89 papers), Direction-of-Arrival Estimation Techniques (84 papers), Distributed Sensor Networks and Detection Algorithms (29 papers), Remote-Sensing Image Classification (24 papers), Target Tracking and Data Fusion in Sensor Networks (24 papers), Microwave Imaging and Scattering Analysis (16 papers) and Ocean Waves and Remote Sensing (15 papers). The work is most often cited by research in Aerospace Engineering (3.5k citations), Signal Processing (1.3k citations), Computational Mathematics (32 citations), Media Technology (427 citations) and Oceanography (418 citations). Jun Liu has collaborated with scholars based in China, United States and Italy. Frequent co-authors include Weijian Liu, Yongliang Wang, Hongbin Li, Braham Himed, Chengpeng Hao, Danilo Orlando, Zijing Zhang, Wenchong Xie, Jian Li and Hongwei Liu. Their work appears in journals such as IEEE Transactions on Signal Processing, Signal Processing, IEEE Transactions on Aerospace and Electronic Systems, IEEE Signal Processing Letters 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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