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Researcher · Zenuity (Sweden) · Sweden

Mina Alibeigi

Mina Alibeigi publishes mostly in Computer Vision and Pattern Recognition, Artificial Intelligence and Automotive Engineering, on topics such as Advanced Neural Network Applications, Domain Adaptation and Few-Shot Learning and Autonomous Vehicle Technology and Safety.

ORCID 0000-0002-5078-0194 OpenAlex
World rank
#2,091,094
of 7,710,434 ranked researchers
Rank in Sweden
#27,052
of 71,437
Works
24
Citations
319
Citations per work
13.3
h-index
8
i10-index 8Top 60% in Computer Vision and Pattern Recognition
Mina Alibeigi

What does Mina Alibeigi research?

Mina Alibeigi's work is mostly in Computer Science (65%), Engineering (8%), Health Professions (6%).

Physical Sciences: 18 works · 76.1% of their workComputer Science: 16 works · 65.0% of their workComputer Vision and Pattern Recognition: 8 works · 33.3% of their workArtificial Intelligence: 8 works · 31.7% of their workEngineering: 2 works · 7.9% of their workAutomotive Engineering: 2 works · 7.9% of their workEnvironmental Science: 1 works · 3.2% of their workEnvironmental Engineering: 1 works · 3.2% of their workEverything else: 3 works · 14.4% of their workHealth Sciences: 2 works · 6.3% of their workHealth Professions: 2 works · 6.3% of their workGeneral Health Professions: 2 works · 6.3% of their workSocial Sciences: 1 works · 3.2% of their workArts and Humanities: 1 works · 3.2% of their workPhilosophy: 1 works · 3.2% of their workTHEIR WORKMina Alibeigi24works
Physical Sciences76%Health Sciences6%Social Sciences3%

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 Science1665.0%
    2. Engineering27.9%
    3. Environmental Science13.2%
  2. Everything else314.4%
    1. Health Professions26.3%
    1. Arts and Humanities13.2%
  1. 1Computer Vision and Pattern Recognition33% of their works
  2. 2Artificial Intelligence32% of their works
  3. 3Automotive Engineering8% of their works
  4. 4General Health Professions6% of their works
  5. 5Environmental Engineering3% of their works
  6. 6Philosophy3% of their works

Research topics

Which keywords describe Mina Alibeigi's research?

The keywords of their largest research topics: Deep Learning, Convolutional Neural Networks, Image Recognition, Machine Learning, Object Detection, Meta-Learning, Autonomous Vehicles and Domain Adaptation.

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.

All 22 words, with their numbers
  1. Deep Learning204 topics
  2. Convolutional Neural Networks122 topics
  3. Image Recognition91 topic
  4. Machine Learning92 topics
  5. Object Detection91 topic
  6. Meta-Learning72 topics
  7. Autonomous Vehicles51 topic
  8. Domain Adaptation51 topic
  9. Neural Networks52 topics
  10. Trajectory Prediction51 topic
  11. Transfer Learning51 topic
  12. Classification42 topics
  13. Differential Privacy41 topic
  14. Federated Learning41 topic
  15. Object Tracking31 topic
  16. Reinforcement Learning31 topic
  17. Robotics31 topic
  18. Visual Tracking31 topic
  19. Extreme Learning Machine21 topic
  20. Feedforward Networks21 topic
  21. Hyperparameter Optimization21 topic
  22. Noisy Labels21 topic

Where does Mina Alibeigi work?

Mina Alibeigi's main affiliation in the publication record is Zenuity (Sweden), Sweden.

How many publications and citations does Mina Alibeigi have?

OpenAlex counts 24 works and 319 citations for Mina Alibeigi, an h-index of 8, ranking #2,091,094 of 7,710,434 researchers worldwide on the quality score.

Ranked on field-normalised 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.

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