Jun-Bao Li

701 citations
50 papers · 489 indexed · h-index 12
Topics
Face and Expression Recognition (21 papers)Image Retrieval and Classification Techniques (12 papers)Remote-Sensing Image Classification (9 papers)
Partner nations
ChinaTaiwanAustralia

In The Last Decade

Jun-Bao Li

45 papers receiving 460 citations

Peers

Jun-Bao Li
Comparison fields: 5 of 75
  • Computer Vision and Pattern Recognition 227
  • Artificial Intelligence 100
  • Media Technology 93
  • Biomedical Engineering 88
  • Control and Systems Engineering 49
Replace Shaopeng Guo with:
Shaopeng Guo China
Saravanan Chandran India
Haibing Wu China
Pengpeng Liu China
Chang Huang China
Zehao Yu China
Sichao Fu China
Tiejun Li China
Jun-Bao Li relative to Shaopeng Guo China Shaopeng Guo's profile →
Citations per field
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Shaopeng Guo · 1×
Citations per year

Countries citing papers authored by Jun-Bao Li

Since Specialization
Citations

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

Fields of papers citing papers by Jun-Bao Li

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Jun-Bao Li

This figure shows the co-authorship network connecting the top 25 collaborators of Jun-Bao Li. A scholar is included among the top collaborators of Jun-Bao Li 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 Jun-Bao Li. Jun-Bao Li 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
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Hyperspectral Image Recognition Using SVM Combined Deep Learning
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9 76
10
The Classification of Synthetic Aperture Radar Image Target Based on Deep Learning.
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11
Overview of Deep Kernel Learning Based Techniques and Applications.
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Optimizing matrix mapping with data dependent kernel for image classification
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About Jun-Bao Li

Jun-Bao Li is a scholar working on Computer Vision and Pattern Recognition, Media Technology and Aerospace Engineering, having authored 50 papers that have together received 489 indexed citations. Recurring topics across this work include Face and Expression Recognition (21 papers), Image Retrieval and Classification Techniques (12 papers) and Remote-Sensing Image Classification (9 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (227 citations), Media Technology (93 citations) and Artificial Intelligence (100 citations). Jun-Bao Li has collaborated with scholars based in China, Taiwan and Australia. Frequent co-authors include Jeng‐Shyang Pan, Zhe‐Ming Lu, Lujia Han, Haiyan Zhang, Minsheng Lu, Yaping Li, Ping Fu, Mingzhu Xu, Huijun Gao and Zhi He. Their work appears in journals such as Bioresource Technology, IEEE Transactions on Image Processing and Expert Systems with Applications.

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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