Jun Han

1.8k citations
84 papers · 1.3k indexed · 1 hit paper · h-index 19

Jun Han

78 papers receiving 1.3k citations

Hit Papers

ACCessory263201220262016202150100150200250

Peers

Jun Han
Comparison fields: 5 of 117
  • Signal Processing 413
  • Information Systems 371
  • Computer Vision and Pattern Recognition 274
  • Computer Science Applications 66
  • Human-Computer Interaction 60
Replace Yi‐Chao Chen with:
Yi‐Chao Chen China
Lei Xie China
Wenchao Huang China
Yanchao Zhao China
Chao Cai China
Yu Gu China
Suhas Mathur United States
Kanchana Thilakarathna Australia
Chenhan Xu United States
Jun Han relative to Yi‐Chao Chen China Yi‐Chao Chen's profile →
Citations per field
00.5×1.6×
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-authorship network

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
#Work
1 20241
2 20240
3 20241
4 20242
5 20237
6 20232
7 20231
8 20231
9 20231
10 20220
11
A Stealthy Location Identification Attack Exploiting Carrier Aggregation in Cellular Networks
20216
12
Acoustics to the Rescue: Physical Key Inference Attack Revisited
20213
13 202075
14 201812
15 201515
16
Cloud terminal: secure access to sensitive applications from untrusted systems
201223
17 20119
18 20101
19 200728
20 20061

About Jun Han

Jun Han is a scholar working on Signal Processing, Computer Vision and Pattern Recognition, Statistics and Probability, Hardware and Architecture and Artificial Intelligence, having authored 84 papers that have together received 1.3k indexed citations. Recurring topics across this work include User Authentication and Security Systems (11 papers), Indoor and Outdoor Localization Technologies (9 papers), Advanced Malware Detection Techniques (8 papers), Ferroelectric and Piezoelectric Materials (7 papers), Digital Media Forensic Detection (6 papers), Anomaly Detection Techniques and Applications (6 papers), Video Surveillance and Tracking Methods (5 papers) and Fuel Cells and Related Materials (5 papers). The work is most often cited by research in Signal Processing (413 citations), Information Systems (371 citations), Computer Vision and Pattern Recognition (274 citations), Computer Science Applications (66 citations) and Human-Computer Interaction (60 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, Hae Young Noh, Le T. Nguyen, Pei Zhang and Shijia Pan. Their work appears in journals such as Journal of Nanoscience and Nanotechnology, Journal of Applied Polymer Science, ACM Transactions on Sensor Networks, Proceedings of the ACM on Interactive Mobile Wearable and Ubiquitous Technologies and Scientific Reports.

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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