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Researcher · FPT University · Vietnam

Phuong-Nam Tran

Phuong-Nam Tran publishes mostly in Computer Vision and Pattern Recognition, Artificial Intelligence and Experimental and Cognitive Psychology, on topics such as Emotion and Mood Recognition, Advanced Neural Network Applications and Handwritten Text Recognition Techniques.

ORCID 0009-0009-6551-9106 OpenAlex
World rank
#4,364,121
of 7,710,434 ranked researchers
Rank in Vietnam
#4,778
of 12,105
Works
34
Citations
147
Citations per work
4.3
h-index
5
i10-index 2Top 87% in Computer Vision and Pattern Recognition
Phuong-Nam Tran

What does Phuong-Nam Tran research?

Phuong-Nam Tran's work is mostly in Computer Science (62%), Engineering (12%), Psychology (11%).

Physical Sciences: 25 works · 74.2% of their workComputer Science: 21 works · 61.8% of their workComputer Vision and Pattern Recognition: 10 works · 29.2% of their workArtificial Intelligence: 10 works · 28.1% of their workSignal Processing: 2 works · 4.5% of their workEngineering: 4 works · 12.4% of their workElectrical and Electronic Engineering: 3 works · 9.0% of their workMedia Technology: 1 works · 3.4% of their workEverything else: 5 works · 14.6% of their workSocial Sciences: 4 works · 11.2% of their workPsychology: 4 works · 11.2% of their workExperimental and Cognitive Psychology: 4 works · 11.2% of their workTHEIR WORKPhuong-Nam Tran34works
Physical Sciences74%Social Sciences11%

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 Science2161.8%
    2. Engineering412.4%
  2. Everything else514.6%
    1. Psychology411.2%
  1. 1Computer Vision and Pattern Recognition29% of their works
  2. 2Artificial Intelligence28% of their works
  3. 3Experimental and Cognitive Psychology11% of their works
  4. 4Electrical and Electronic Engineering9% of their works
  5. 5Signal Processing4% of their works
  6. 6Media Technology3% of their works

Research topics

Which keywords describe Phuong-Nam Tran's research?

The keywords of their largest research topics: Deep Learning, Emotion Recognition, Convolutional Neural Networks, Facial Expression, Multimodal Data, Machine Learning, Neural Networks 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 Learning265 topics
  2. Emotion Recognition142 topics
  3. Convolutional Neural Networks112 topics
  4. Facial Expression101 topic
  5. Multimodal Data101 topic
  6. Machine Learning82 topics
  7. Neural Networks82 topics
  8. Image Recognition61 topic
  9. Object Detection61 topic
  10. Handwriting Recognition51 topic
  11. Text Detection51 topic
  12. Differential Privacy41 topic
  13. Federated Learning41 topic
  14. Opinion Mining41 topic
  15. Sentiment Analysis41 topic
  16. Image Captioning31 topic
  17. Markov Decision Processes31 topic
  18. Modulation Classification31 topic
  19. Spoken Dialogue Systems31 topic
  20. Visual Question Answering31 topic
  21. Wireless Communications31 topic

Where does Phuong-Nam Tran work?

Phuong-Nam Tran's main affiliation in the publication record is FPT University, Vietnam.

How many publications and citations does Phuong-Nam Tran have?

OpenAlex counts 34 works and 147 citations for Phuong-Nam Tran, an h-index of 5, ranking #4,364,121 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.

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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