Jun Bai

728 citations
25 papers · 550 · h-index 8

Impact in

Papers in

Jun Bai

22 papers receiving 534 citations

Peers

Jun Bai
Comparison fields: 5 of 72
  • Media Technology 251
  • Computer Vision and Pattern Recognition 224
  • Health Informatics 14
  • Artificial Intelligence 157
  • Ocean Engineering 75
Replace Çağlar Şenaras with:
Çağlar Şenaras United States
Laila Bashmal Saudi Arabia
Esam Othman Saudi Arabia
Camille Kurtz France
Alex Levinshtein Canada
Zhongling Huang China
Puhua Chen China
Liye Mei China
Jeya Maria Jose Valanarasu United States
Hüseyin Kusetoğulları Sweden
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Citations per year

Countries citing papers authored by Jun Bai

Since Specialization
Citations

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

Fields of papers citing papers by Jun Bai

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 25 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2017236
2 2021104
3 201256
4 202138
5 201732
6 201522
7 201719
8 20107
9 20225
10 20175
11 20124
12 20114
13 20163
14 20053
15
Study on hyperspectral image technology based on manifold fuzzy clustering for pork quality classification.
20152
16 20232
17 20172
18 20142
19 20241
20
Research on Characteristics of Ship Wake Noise and Simulation
20091

About Jun Bai

Jun Bai is a scholar working on Computer Vision and Pattern Recognition, Media Technology, Signal Processing, Artificial Intelligence and Atmospheric Science, having authored 25 papers that have together received 550 indexed citations. Recurring topics across this work include Advanced Image and Video Retrieval Techniques (6 papers), Remote-Sensing Image Classification (5 papers), Digital Radiography and Breast Imaging (2 papers), Image Retrieval and Classification Techniques (2 papers), AI in cancer detection (2 papers), Advanced Image Fusion Techniques (2 papers), Advanced Measurement and Detection Methods (2 papers) and Advanced Neural Network Applications (2 papers). The work is most often cited by research in Media Technology (251 citations), Computer Vision and Pattern Recognition (224 citations), Health Informatics (14 citations), Artificial Intelligence (157 citations) and Ocean Engineering (75 citations). Jun Bai has collaborated with scholars based in China and United States. Frequent co-authors include Chunhong Pan, Shiming Xiang, Bin Fan, Lingfeng Wang, Tianyu Wang, Sheida Nabavi, Clifford Yang, Feifei Zhao, Yi Zeng and Limin Shi. Their work appears in journals such as ISPRS Journal of Photogrammetry and Remote Sensing, BMC Bioinformatics, Cognitive Computation, IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing and Medical Image Analysis.

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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