Bryan Nousain

788 citations
8 papers · 596 indexed · 1 hit paper · h-index 5

Impact in

Papers in

Bryan Nousain

8 papers receiving 572 citations

Hit Papers

Deep Learning for RF Device Fingerprinting in Cognitive Communication Networks 2018 · 377 citations
3772018202620202023100200300

Peers

Bryan Nousain
Comparison fields: 5 of 34
  • Artificial Intelligence 515
  • Signal Processing 155
  • Computer Vision and Pattern Recognition 143
  • Aerospace Engineering 156
  • Electrical and Electronic Engineering 265
Replace Guanxiong Shen with:
Guanxiong Shen United Kingdom
Mauro Belgiovine United States
Fanggang Wang China
Jeyanthi Hall Canada
Kemal Davaslıoğlu United States
Caidan Zhao China
Sebastian Dörner Germany
Haji M. Furqan Türkiye
Evangelos Vlachos Greece
Haijun Tan China
Bryan Nousain relative to Guanxiong Shen United Kingdom Guanxiong Shen's profile →
Citations per field
00.5×8.5×
Guanxiong Shen · 1×
Citations per year

Countries citing papers authored by Bryan Nousain

Since Specialization
Citations

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

Fields of papers citing papers by Bryan Nousain

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network

The 5 scholars most cited alongside Bryan Nousain, 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 Bryan Nousain Line = papers co-authored together Bryan Nousain links everyone, so they are left out of the graph.

All Works

8 of 8 papers shown
#Work
1 201918
2 201918
3 201915
4 20181
5
Deep Learning for RF Device Fingerprinting in Cognitive Communication Networks
Hit paper breakdown →
2018377
6 20121
7 20114
8 2011162

About Bryan Nousain

Bryan Nousain is a scholar working on Signal Processing, Computer Vision and Pattern Recognition, Artificial Intelligence, Media Technology and Computational Mechanics, having authored 8 papers that have together received 596 indexed citations. Recurring topics across this work include Wireless Signal Modulation Classification (5 papers), Speech and Audio Processing (2 papers), Digital Media Forensic Detection (2 papers), Blind Source Separation Techniques (2 papers), Image and Signal Denoising Methods (1 paper), Digital Filter Design and Implementation (1 paper), Neural Networks and Applications (1 paper) and Advanced Adaptive Filtering Techniques (1 paper). The work is most often cited by research in Artificial Intelligence (515 citations), Signal Processing (155 citations), Computer Vision and Pattern Recognition (143 citations), Aerospace Engineering (156 citations) and Electrical and Electronic Engineering (265 citations). Bryan Nousain has collaborated with scholars based in United States. Frequent co-authors include George Stantchev, Mark K. Hinders, Jonathan M. Nichols, F. Bucholtz and C. G. Davis. Their work appears in journals such as IEEE Journal of Selected Topics in Signal Processing, IEEE Transactions on Signal Processing, Expert Systems with Applications, IEEE Transactions on Industrial Electronics and Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE.

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.

Explore authors with similar magnitude of impact

Rankless by CCL
2026