Jun Han

84 papers receiving 1.4k citations

Jun Han's Hit Papers

ACCessory 2012 · 301 citations
3010+4+9Years since publication100200300

Peers

Jun Han
Comparison fields: 5 of 114
  • Signal Processing 473
  • Information Systems 435
  • Computer Vision and Pattern Recognition 286
  • Computer Science Applications 75
  • Human-Computer Interaction 69
Replace Yi‐Chao Chen with:
Yi‐Chao Chen China
Lei Xie China
Yanchao Zhao China
Kumar Yelamarthi United States
Yu Gu China
Chao Cai China
Wenchao Huang China
Chenhan Xu United States
Mohammad S. Khan United States
Jun Han relative to Yi‐Chao Chen China Yi‐Chao Chen's profile →
Citations per field
00.5×1.7×
Yi‐Chao Chen · 1×
Citations per year

Countries citing papers authored by Jun Han

Since Specialization
Citations

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

Fields of papers citing papers by Jun Han

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 91 papers — load more, or switch the sort, to bring in the rest.

#Work
1
ACCessory
Hit paper breakdown →
2012301
2 2012136
3 202077
4 201875
5 202064
6 201653
7 201748
8 201743
9 201841
10 201638
11 201337
12 201734
13 200731
14 200729
15 201328
16
Cloud terminal: secure access to sensitive applications from untrusted systems
201226
17 201822
18 201922
19 201821
20 201416

About Jun Han

Jun Han is a scholar working on Electrical and Electronic Engineering, Computer Vision and Pattern Recognition, Artificial Intelligence, Information Systems and Signal Processing, having authored 91 papers that have together received 1.4k indexed citations. Recurring topics across this work include User Authentication and Security Systems (12 papers), Advanced Malware Detection Techniques (10 papers), Indoor and Outdoor Localization Technologies (9 papers), Digital Media Forensic Detection (7 papers), Ferroelectric and Piezoelectric Materials (7 papers), Anomaly Detection Techniques and Applications (6 papers), Context-Aware Activity Recognition Systems (5 papers) and Statistical Methods and Bayesian Inference (5 papers). The work is most often cited by research in Signal Processing (473 citations), Information Systems (435 citations), Computer Vision and Pattern Recognition (286 citations), Computer Science Applications (75 citations) and Human-Computer Interaction (69 citations). Jun Han has collaborated with scholars based in South Korea, United States and Singapore. Frequent co-authors include Adrian Perrig, Emmanuel Owusu, Joy Zhang, Sauvik Das, Patrick Tague, Albert Jin Chung, Le T. Nguyen, Hae Young Noh, Pei Zhang and Shijia Pan. Their work appears in journals such as Journal of Nanoscience and Nanotechnology, Journal of Applied Polymer Science, Proceedings of the ACM on Interactive Mobile Wearable and Ubiquitous Technologies, ACM Transactions on Sensor Networks and International Immunopharmacology.

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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