Junyang Qiu

781 citations
21 papers · 463 · 1 hit paper · h-index 11

Impact in

Papers in

Junyang Qiu

19 papers receiving 449 citations

Hit Papers

A Survey of Android Malware Detection with Deep Neural Models 2020 · 204 citations
2040+2+4Years since publication50100150200

Peers

Junyang Qiu
Comparison fields: 5 of 59
  • Signal Processing 270
  • Software 63
  • Computer Networks and Communications 265
  • Information Systems 183
  • Artificial Intelligence 191
Replace Asankhaya Sharma with:
Asankhaya Sharma Singapore
Qiujian Lv China
Yunhan Jia United States
Weizhong Qiang China
Qinkai Zheng China
Youngsoo Kim South Korea
K. V. S. V. N. Raju India
P. Vinod India
Reza Farivar United States
Junyang Qiu relative to Asankhaya Sharma Singapore Asankhaya Sharma's profile →
Citations per field
00.5×1.5×2.0×
Asankhaya Sharma · 1×
Citations per year

Countries citing papers authored by Junyang Qiu

Since Specialization
Citations

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

Fields of papers citing papers by Junyang Qiu

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 21 papers — load more, or switch the sort, to bring in the rest.

#Work
1
A Survey of Android Malware Detection with Deep Neural Models
Hit paper breakdown →
2020204
2 202049
3 201933
4 201931
5 202228
6 201823
7 201922
8 201914
9 201913
10 202012
11 202111
12 20207
13 20206
14 20223
15 20162
16 20241
17 20191
18 20241
19 20141
20 20231

About Junyang Qiu

Junyang Qiu is a scholar working on Artificial Intelligence, Computer Networks and Communications, Signal Processing, Computer Vision and Pattern Recognition and Information Systems, having authored 21 papers that have together received 463 indexed citations. Recurring topics across this work include Network Security and Intrusion Detection (7 papers), Advanced Malware Detection Techniques (6 papers), Video Surveillance and Tracking Methods (4 papers), Complex Network Analysis Techniques (3 papers), Anomaly Detection Techniques and Applications (3 papers), Spam and Phishing Detection (2 papers), Visual Attention and Saliency Detection (2 papers) and Digital and Cyber Forensics (2 papers). The work is most often cited by research in Signal Processing (270 citations), Software (63 citations), Computer Networks and Communications (265 citations), Information Systems (183 citations) and Artificial Intelligence (191 citations). Junyang Qiu has collaborated with scholars based in China and Australia. Frequent co-authors include Lei Pan, Wei Luo, Yang Xiang, ‪Surya Nepal‬, Jun Zhang, Zhisong Pan, Nan Sun, Paul Rimba, Guanjun Lin and Xingyu Zhou. Their work appears in journals such as IEEE Access, Neurocomputing, Information and Software Technology, IEEE Transactions on Cybernetics and Semiconductor Science and Technology.

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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