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Researcher · Anhui Polytechnic University · China

Bing Cai

Bing Cai publishes mostly in Computer Vision and Pattern Recognition, Computational Mathematics and Artificial Intelligence, on topics such as Face and Expression Recognition, Tensor decomposition and applications and Advanced Image and Video Retrieval Techniques.

ORCID 0000-0002-2360-2579 OpenAlex
World rank
#1,584,914
of 7,710,434 ranked researchers
Rank in China
#238,087
of 978,568
Works
19
Citations
225
Citations per work
11.8
h-index
10
i10-index 10Top 45% in Computer Vision and Pattern Recognition
Bing Cai

What does Bing Cai research?

Bing Cai's work is mostly in Computer Science (56%), Mathematics (13%), Engineering (7%).

Physical Sciences: 14 works · 76.3% of their workComputer Science: 11 works · 56.3% of their workComputer Vision and Pattern Recognition: 8 works · 43.6% of their workArtificial Intelligence: 2 works · 12.7% of their workMathematics: 2 works · 12.7% of their workComputational Mathematics: 2 works · 12.7% of their workEngineering: 1 works · 7.3% of their workComputational Mechanics: 1 works · 7.3% of their workEverything else: 3 works · 14.6% of their workSocial Sciences: 2 works · 9.1% of their workSocial Sciences: 1 works · 5.5% of their workUrban Studies: 1 works · 5.5% of their workDecision Sciences: 1 works · 3.6% of their workManagement Science and Operations Research: 1 works · 3.6% of their workTHEIR WORKBing Cai19works
Physical Sciences76%Social Sciences9%

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 Science1156.3%
    2. Mathematics212.7%
    3. Engineering17.3%
  2. Everything else314.6%
    1. Social Sciences15.5%
    2. Decision Sciences13.6%
  1. 1Computer Vision and Pattern Recognition44% of their works
  2. 2Computational Mathematics13% of their works
  3. 3Artificial Intelligence13% of their works
  4. 4Computational Mechanics7% of their works
  5. 5Urban Studies6% of their works
  6. 6Management Science and Operations Research4% of their works

Research topics

Which keywords describe Bing Cai's research?

The keywords of their largest research topics: Sparse Representation, Feature Selection, Dimensionality Reduction, Face Recognition, Multilinear Algebra, Tensor Decomposition, Deep Learning and Compressed Sensing.

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 19 words, with their numbers
  1. Sparse Representation182 topics
  2. Feature Selection162 topics
  3. Dimensionality Reduction141 topic
  4. Face Recognition141 topic
  5. Multilinear Algebra71 topic
  6. Tensor Decomposition71 topic
  7. Deep Learning62 topics
  8. Compressed Sensing41 topic
  9. Feature Matching41 topic
  10. Local Descriptors41 topic
  11. Signal Recovery41 topic
  12. Clustering Algorithms31 topic
  13. K-means31 topic
  14. Spatial Network Analysis31 topic
  15. Urban Structure31 topic
  16. Multi-label Learning21 topic
  17. Object Tracking21 topic
  18. Text Classification21 topic
  19. Visual Tracking21 topic

Where does Bing Cai work?

Bing Cai's main affiliation in the publication record is Anhui Polytechnic University, China.

How many publications and citations does Bing Cai have?

OpenAlex counts 19 works and 225 citations for Bing Cai, an h-index of 10, ranking #1,584,914 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 Bing Cai

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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