Fengbo Ren

50 papers receiving 1.3k citations

Fengbo Ren's Hit Papers

Learning in the Frequency Domain 2020 · 326 citations
3260+2+4Years since publication100200300

Peers

Fengbo Ren
Comparison fields: 5 of 124
  • Computer Vision and Pattern Recognition 444
  • Hardware and Architecture 103
  • Media Technology 106
  • Computational Mathematics 7
  • Polymers and Plastics 112
Replace Dongjoo Shin with:
Dongjoo Shin South Korea
Rajesh Mehra India
Jiaji Wu China
Shan Gai China
Qi Wei China
Amit Kumar Mishra South Africa
Xiaojin Zhao China
Jing Pei China
Hongxin Zhang China
Fengbo Ren relative to Dongjoo Shin South Korea Dongjoo Shin's profile →
Citations per field
00.5×4.5×
Dongjoo Shin · 1×
Citations per year

Countries citing papers authored by Fengbo Ren

Since Specialization
Citations

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

Fields of papers citing papers by Fengbo Ren

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 50 papers — load more, or switch the sort, to bring in the rest.

#Work
1
Learning in the Frequency Domain
Hit paper breakdown →
2020326
2 2014191
3 202094
4 201867
5 201267
6 201461
7 201056
8 201855
9 201850
10 201737
11 202028
12 201326
13 201622
14 202121
15 201721
16 201520
17 201219
18 201518
19 201817
20 201316

About Fengbo Ren

Fengbo Ren is a scholar working on Computer Vision and Pattern Recognition, Electrical and Electronic Engineering, Computational Mechanics, Biomedical Engineering and Signal Processing, having authored 50 papers that have together received 1.4k indexed citations. Recurring topics across this work include Sparse and Compressive Sensing Techniques (11 papers), Advanced Neural Network Applications (11 papers), Advanced Memory and Neural Computing (7 papers), Blind Source Separation Techniques (6 papers), Analog and Mixed-Signal Circuit Design (5 papers), Machine Learning and ELM (4 papers), Semiconductor materials and devices (4 papers) and Magnetic properties of thin films (3 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (444 citations), Hardware and Architecture (103 citations), Media Technology (106 citations), Computational Mathematics (7 citations) and Polymers and Plastics (112 citations). Fengbo Ren has collaborated with scholars based in United States, China and Singapore. Frequent co-authors include Dejan Marković, Yixing Li, Yuhao Wang, Kai Xu, Minghai Qin, Yen-Kuang Chen, Fei Sun, Richard Dorrance, Zichuan Liu and Hao Yu. Their work appears in journals such as IEEE Transactions on Biomedical Circuits and Systems, IEEE Transactions on Electron Devices, Organic & Biomolecular Chemistry, ACM Journal on Emerging Technologies in Computing Systems and IEEE/ACM Transactions on Computational Biology and Bioinformatics.

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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