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Researcher · Dalian Polytechnic University · China

Jun Mou

Jun Mou publishes mostly in Computer Vision and Pattern Recognition, Statistical and Nonlinear Physics and Electrical and Electronic Engineering, on topics such as Chaos-based Image/Signal Encryption, Advanced Memory and Neural Computing and Chaos control and synchronization.

ORCID 0000-0002-7774-2833 OpenAlex
World rank
#15,685
of 7,710,434 ranked researchers
Rank in China
#888
of 978,568
Works
235
Citations
7.4k
Citations per work
31.3
h-index
49
i10-index 135Top 1.2% in Computer Vision and Pattern Recognition
Jun Mou

What does Jun Mou research?

Jun Mou's work is mostly in Computer Science (39%), Physics and Astronomy (20%), Engineering (12%).

Physical Sciences: 167 works · 71.1% of their workComputer Science: 93 works · 39.4% of their workComputer Vision and Pattern Recognition: 56 works · 24.0% of their workComputer Networks and Communications: 20 works · 8.7% of their workArtificial Intelligence: 16 works · 6.7% of their workPhysics and Astronomy: 46 works · 19.6% of their workStatistical and Nonlinear Physics: 46 works · 19.6% of their workEngineering: 28 works · 12.1% of their workElectrical and Electronic Engineering: 28 works · 12.1% of their workEverything else: 55 works · 23.2% of their workLife Sciences: 13 works · 5.7% of their workNeuroscience: 13 works · 5.7% of their workCognitive Neuroscience: 13 works · 5.7% of their workTHEIR WORKJun Mou235works
Life Sciences6%Physical Sciences71%

Their six largest subfields, inside their fields and domains; the grey slice is everything else they publish. The interactive view splits every one of their works down to single topics.

The fields and subfields, with their numbers
    1. Computer Science9339.4%
    2. Physics and Astronomy4619.6%
    3. Engineering2812.1%
  2. Everything else5523.2%
    1. Neuroscience135.7%
  1. 1Computer Vision and Pattern Recognition24% of their works
  2. 2Statistical and Nonlinear Physics20% of their works
  3. 3Electrical and Electronic Engineering12% of their works
  4. 4Computer Networks and Communications9% of their works
  5. 5Artificial Intelligence7% of their works
  6. 6Cognitive Neuroscience6% of their works

Research topics

Which keywords describe Jun Mou's research?

The keywords of their largest research topics: Chaos, Synchronization, Neural Networks, Chaotic Maps, Image Encryption, Memristor, Neuromorphic Computing and Deep Learning.

Size is their works in the topics tagged with each word, from their 8 largest topics. Each links to the topic it comes from most. The words come from the keyword list OpenAlex gives each topic, not from the text of the papers, so a word can appear that none of the papers uses.

All 20 words, with their numbers
  1. Chaos1542 topics
  2. Synchronization1353 topics
  3. Neural Networks1283 topics
  4. Chaotic Maps881 topic
  5. Image Encryption881 topic
  6. Memristor721 topic
  7. Neuromorphic Computing721 topic
  8. Deep Learning712 topics
  9. Complex Systems661 topic
  10. Nonlinear Dynamics661 topic
  11. Brownian Motors541 topic
  12. Stochastic Resonance541 topic
  13. Reversible Data Embedding511 topic
  14. Steganography511 topic
  15. Complex Networks361 topic
  16. Dynamical Systems361 topic
  17. Cortical Networks331 topic
  18. Neuronal Oscillations331 topic
  19. Backpropagation Learning201 topic
  20. Self-Organizing Maps201 topic

Where does Jun Mou work?

Jun Mou's main affiliation in the publication record is Dalian Polytechnic University, China.

How many publications and citations does Jun Mou have?

OpenAlex counts 235 works and 7,353 citations for Jun Mou, an h-index of 49, ranking #15,685 of 7,710,434 researchers worldwide on the quality score.

Ranked on field-normalised citation excellence (50%), output (30%) and citations (20%). Counts come from OpenAlex author records, which occasionally merge different people who share a name or split one person into several.

Other researchers named Jun Mou

Papers, co-authors, who cited this work and researchers on the nearest topics have tabs of their own, above. Is this your page? Claim it with your ORCID iD, or request a correction or removal.

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