Tao Jin

678 citations
28 papers · 530 indexed · h-index 9
Topics
Advanced Photonic Communication Systems (5 papers)Optical Network Technologies (3 papers)Multimodal Machine Learning Applications (3 papers)
Partner nations
ChinaSingaporeBangladesh

In The Last Decade

Tao Jin

26 papers receiving 506 citations

Peers

Tao Jin
Comparison fields: 5 of 54
  • Computer Vision and Pattern Recognition 211
  • Electrical and Electronic Engineering 153
  • Signal Processing 136
  • Aerospace Engineering 108
  • Media Technology 107
Replace Martin Landmann with:
Martin Landmann Germany
Ching-Te Chiu Taiwan
Yufu Qu China
Yuzhi Zhao China
Christel-Loïc Tisse France
Sangjun Park South Korea
John Macdonald United Kingdom
Yonghui Huang China
Ahmad Mahmoudi-Aznaveh Iran
B. Fisher United States
Tao Jin relative to Martin Landmann Germany Martin Landmann's profile →
Citations per field
00.5×1.5×2.2×
Martin Landmann · 1×
Citations per year

Countries citing papers authored by Tao Jin

Since Specialization
Citations

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

Fields of papers citing papers by Tao Jin

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Tao Jin

This figure shows the co-authorship network connecting the top 25 collaborators of Tao Jin. A scholar is included among the top collaborators of Tao Jin based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Tao Jin. Tao Jin is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
#WorkIndexed citations
1 1
2 7
3 0
4 10
5 4
6 12
7 2
8 8
9 27
10 5
11 7
12 158
13
Control of Transformer Noise Using Independent Planar Virtual Sound Barrier
1
14 18
15 26
16 27
17
Bandpass active filter designed for rapid unbalance measurement
0
18 2
19 23
20 1

About Tao Jin

Tao Jin is a scholar working on Acoustics and Ultrasonics, General Engineering and Computer Vision and Pattern Recognition, having authored 28 papers that have together received 530 indexed citations. Recurring topics across this work include Advanced Photonic Communication Systems (5 papers), Optical Network Technologies (3 papers) and Multimodal Machine Learning Applications (3 papers). The work is most often cited by research in Signal Processing (136 citations), Media Technology (107 citations) and Computer Vision and Pattern Recognition (211 citations). Tao Jin has collaborated with scholars based in China, Singapore and Bangladesh. Frequent co-authors include Xinwei Zhao, Zhiguo Shi, Yujie Gu, Chengwei Zhou, Xidong Wu, Yimin D. Zhang, Xinwei Zhao, Xuguang Huang, Jia Zhu and Ying Zhang. Their work appears in journals such as Optics Letters, Optics Express and Neurocomputing.

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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