Jun Huang

1.9k citations
89 papers · 1.4k indexed · h-index 17

Jun Huang

81 papers receiving 1.3k citations

Peers

Jun Huang
Comparison fields: 5 of 112
  • Computer Vision and Pattern Recognition 547
  • Artificial Intelligence 848
  • Information Systems 342
  • Media Technology 47
  • Computational Mathematics 3
Replace Jagendra Singh with:
Jagendra Singh India
Waqas Haider Bangyal Pakistan
César García‐Osorio Spain
Luiza de Macedo Mourelle Brazil
Prachi Agrawal India
Jing Tang China
Renato Cordeiro de Amorim United Kingdom
Olga Kurasova Lithuania
Tommy Dang United States
Jun Huang relative to Jagendra Singh India Jagendra Singh's profile →
Citations per field
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Jagendra Singh · 1×
Citations per year

Countries citing papers authored by Jun Huang

Since Specialization
Citations

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

Fields of papers citing papers by Jun Huang

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network

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

All Works

20 of 20 papers shown
#Work
1 20241
2 20241
3 20242
4 20241
5 20240
6 20245
7 202313
8 202314
9 20234
10 202221
11 20221
12 20221
13 20172
14
Exploration of tunneling-induced surface settlements in soils by the reciprocal theorem
20153
15 20139
16
A novel detecting method of electric shock signal based on wavelet transform and chaotic theory
20113
17
Simulated experiment on effects of soil bulk density on soil water holding capacity.
201013
18
Simulated experiment on effect of soil bulk density on soil infiltration capacity.
200937
19
Hot Targets Enhancement for Color Fusion of Visible and Infrared Images
20081
20
RECENT DEVELOPMENTS IN CONCEPTUAL/PRELIMINARY DESIGN OPTIMIZATION OF AIRCRAFT
20005

About Jun Huang

Jun Huang is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition and Organizational Behavior and Human Resource Management, having authored 89 papers that have together received 1.4k indexed citations. Recurring topics across this work include Text and Document Classification Technologies (21 papers), Spam and Phishing Detection (10 papers), Image Retrieval and Classification Techniques (8 papers), Web Data Mining and Analysis (8 papers), Facility Location and Emergency Management (8 papers), Machine Learning in Bioinformatics (7 papers), Advanced Image and Video Retrieval Techniques (7 papers) and Imbalanced Data Classification Techniques (6 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (547 citations), Artificial Intelligence (848 citations) and Information Systems (342 citations). Jun Huang has collaborated with scholars based in China, United States and United Kingdom. Frequent co-authors include Qingming Huang, Guorong Li, Xindong Wu, Xiao Zheng, Weigang Zhang, Shuhui Wang, Feng Qin, Zhe Xue, Haibo Wang and Liang Zhang. Their work appears in journals such as SHILAP Revista de lepidopterología, Expert Systems with Applications and IEEE Access.

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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