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Researcher · Tencent (China) · China

Jinlong Peng

Jinlong Peng publishes mostly in Computer Vision and Pattern Recognition, Artificial Intelligence and Aerospace Engineering, on topics such as Video Surveillance and Tracking Methods, Advanced Neural Network Applications and Anomaly Detection Techniques and Applications.

ORCID 0009-0003-1887-6406 OpenAlex
World rank
#551,218
of 7,710,434 ranked researchers
Rank in China
#69,269
of 978,568
Works
66
Citations
1.3k
Citations per work
19.1
h-index
15
i10-index 22Top 23% in Computer Vision and Pattern Recognition
Jinlong Peng

What does Jinlong Peng research?

Jinlong Peng's work is mostly in Computer Science (70%), Engineering (6%), Earth and Planetary Sciences (3%).

Physical Sciences: 52 works · 78.7% of their workComputer Science: 47 works · 70.5% of their workComputer Vision and Pattern Recognition: 31 works · 47.0% of their workArtificial Intelligence: 12 works · 17.5% of their workComputer Graphics and Computer-Aided Design: 2 works · 3.3% of their workSignal Processing: 2 works · 2.7% of their workEngineering: 4 works · 5.5% of their workAerospace Engineering: 4 works · 5.5% of their workEarth and Planetary Sciences: 2 works · 2.7% of their workGeology: 2 works · 2.7% of their workEverything else: 14 works · 21.3% of their workTHEIR WORKJinlong Peng66works
Physical Sciences79%

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 Science4770.5%
    2. Engineering45.5%
    3. Earth and Planetary Sciences22.7%
  2. Everything else1421.3%
  1. 1Computer Vision and Pattern Recognition47% of their works
  2. 2Artificial Intelligence18% of their works
  3. 3Aerospace Engineering6% of their works
  4. 4Computer Graphics and Computer-Aided Design3% of their works
  5. 5Geology3% of their works
  6. 6Signal Processing3% of their works

Research topics

Which keywords describe Jinlong Peng's research?

The keywords of their largest research topics: Deep Learning, Convolutional Neural Networks, Neural Networks, Object Tracking, Representation Learning, Unsupervised Learning, Visual Tracking and Image Recognition.

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 21 words, with their numbers
  1. Deep Learning546 topics
  2. Convolutional Neural Networks252 topics
  3. Neural Networks233 topics
  4. Object Tracking131 topic
  5. Representation Learning132 topics
  6. Unsupervised Learning132 topics
  7. Visual Tracking131 topic
  8. Image Recognition121 topic
  9. Object Detection121 topic
  10. Anomaly Detection101 topic
  11. Unsupervised101 topic
  12. Domain Adaptation71 topic
  13. Saliency Detection71 topic
  14. Transfer Learning71 topic
  15. Visual Attention71 topic
  16. Computer Graphics61 topic
  17. Feature Matching61 topic
  18. Generative Adversarial Networks61 topic
  19. Image Synthesis61 topic
  20. Local Descriptors61 topic
  21. Visualization61 topic

Where does Jinlong Peng work?

Jinlong Peng's main affiliation in the publication record is Tencent (China), China.

How many publications and citations does Jinlong Peng have?

OpenAlex counts 66 works and 1,260 citations for Jinlong Peng, an h-index of 15, ranking #551,218 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 Jinlong Peng

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.

Discussion

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