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Researcher · Siemens (United States) · United States

Shaohua Kevin Zhou

Shaohua Kevin Zhou publishes mostly in Computer Vision and Pattern Recognition, Mechanics of Materials and Molecular Biology, on topics such as Medical Image Segmentation Techniques, AI in cancer detection and Non-Destructive Testing Techniques.

ORCID 0000-0002-0973-7231 OpenAlex
World rank
#2,700,872
of 7,710,434 ranked researchers
Rank in United States
#787,803
of 1,627,098
Works
34
Citations
694
Citations per work
20.4
h-index
12
i10-index 13Top 34% in Computer Vision and Pattern Recognition
Shaohua Kevin Zhou

What does Shaohua Kevin Zhou research?

Shaohua Kevin Zhou's work is mostly in Computer Science (30%), Engineering (26%), Biochemistry, Genetics and Molecular Biology (8%).

Physical Sciences: 19 works · 56.2% of their workComputer Science: 10 works · 29.7% of their workComputer Vision and Pattern Recognition: 8 works · 22.3% of their workArtificial Intelligence: 3 works · 7.4% of their workEngineering: 9 works · 26.5% of their workMechanics of Materials: 5 works · 13.8% of their workMechanical Engineering: 3 works · 7.4% of their workBiomedical Engineering: 2 works · 5.3% of their workEverything else: 12 works · 35.3% of their workLife Sciences: 3 works · 8.5% of their workBiochemistry, Genetics and Molecular Biology: 3 works · 8.5% of their workMolecular Biology: 3 works · 8.5% of their workTHEIR WORKShaohua KevinZhou34works
Life Sciences8%Physical Sciences56%

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 Science1029.7%
    2. Engineering926.5%
  2. Everything else1235.3%
    1. Biochemistry, Genetics and Molecular Biology38.5%
  1. 1Computer Vision and Pattern Recognition22% of their works
  2. 2Mechanics of Materials14% of their works
  3. 3Molecular Biology8% of their works
  4. 4Artificial Intelligence7% of their works
  5. 5Mechanical Engineering7% of their works
  6. 6Biomedical Engineering5% of their works

Research topics

Which keywords describe Shaohua Kevin Zhou's research?

The keywords of their largest research topics: Deep Learning, Medical Image Analysis, Machine Learning, Convolutional Neural Networks, Feature Extraction, Graph Cuts, Image Segmentation and Computer-Aided Detection.

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 21 words, with their numbers
  1. Deep Learning204 topics
  2. Medical Image Analysis204 topics
  3. Machine Learning184 topics
  4. Convolutional Neural Networks123 topics
  5. Feature Extraction92 topics
  6. Graph Cuts71 topic
  7. Image Segmentation71 topic
  8. Computer-Aided Detection61 topic
  9. Eddy Current Testing61 topic
  10. Histopathology Images61 topic
  11. Non-Destructive Evaluation61 topic
  12. Fatigue Crack Closure41 topic
  13. Fracture Toughness Testing41 topic
  14. Spine Segmentation41 topic
  15. Vertebrae Detection41 topic
  16. Content-Based Image Retrieval31 topic
  17. Image Recognition31 topic
  18. Leukemia Classification31 topic
  19. Malaria Parasite Detection31 topic
  20. Object Detection31 topic
  21. Shape Matching31 topic

Where does Shaohua Kevin Zhou work?

Shaohua Kevin Zhou's main affiliation in the publication record is Siemens (United States), United States.

How many publications and citations does Shaohua Kevin Zhou have?

OpenAlex counts 34 works and 694 citations for Shaohua Kevin Zhou, an h-index of 12, ranking #2,700,872 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.

Discussion

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