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Researcher · University of Electronic Science and Technology of China · China

Ting‐Zhu Huang

Ting‐Zhu Huang publishes mostly in Computer Vision and Pattern Recognition, Computational Theory and Mathematics and Computational Mechanics, on topics such as Matrix Theory and Algorithms, Image and Signal Denoising Methods and Sparse and Compressive Sensing Techniques.

ORCID 0000-0001-7766-230X OpenAlex
World rank
#569,577
of 7,710,434 ranked researchers
Rank in China
#72,033
of 978,568
Works
730
Citations
13k
Citations per work
18.3
h-index
58
i10-index 282Top 0.7% in Computer Vision and Pattern Recognition
Ting‐Zhu Huang

What does Ting‐Zhu Huang research?

Ting‐Zhu Huang's work is mostly in Computer Science (31%), Engineering (24%), Mathematics (9%).

Physical Sciences: 464 works · 63.5% of their workComputer Science: 226 works · 30.9% of their workComputer Vision and Pattern Recognition: 116 works · 15.9% of their workComputational Theory and Mathematics: 110 works · 15.0% of their workEngineering: 172 works · 23.5% of their workComputational Mechanics: 67 works · 9.2% of their workMedia Technology: 58 works · 8.0% of their workElectrical and Electronic Engineering: 46 works · 6.3% of their workMathematics: 66 works · 9.1% of their workNumerical Analysis: 66 works · 9.1% of their workEverything else: 266 works · 36.5% of their workTHEIR WORKTing‐Zhu Huang730works
Physical Sciences64%

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 Science22630.9%
    2. Engineering17223.5%
    3. Mathematics669.1%
  2. Everything else26636.5%
  1. 1Computer Vision and Pattern Recognition16% of their works
  2. 2Computational Theory and Mathematics15% of their works
  3. 3Computational Mechanics9% of their works
  4. 4Numerical Analysis9% of their works
  5. 5Media Technology8% of their works
  6. 6Electrical and Electronic Engineering6% of their works

Research topics

Which keywords describe Ting‐Zhu Huang's research?

The keywords of their largest research topics: Sparse Representation, Matrix Computations, Numerical Linear Algebra, Wavelet Transform, Deep Learning, Convex Optimization, Image Denoising and Sparse Representations.

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 20 words, with their numbers
  1. Sparse Representation2983 topics
  2. Matrix Computations2891 topic
  3. Numerical Linear Algebra2891 topic
  4. Wavelet Transform2792 topics
  5. Deep Learning2432 topics
  6. Convex Optimization2232 topics
  7. Image Denoising1771 topic
  8. Sparse Representations1771 topic
  9. Compressed Sensing1301 topic
  10. Signal Recovery1301 topic
  11. Electromagnetic Scattering1241 topic
  12. Integral Equation Methods1241 topic
  13. Image Fusion1021 topic
  14. Multispectral1021 topic
  15. Optimization Software931 topic
  16. Semidefinite Programming931 topic
  17. Image661 topic
  18. Super-Resolution661 topic
  19. Fiber Bragg Grating611 topic
  20. Spectral Amplitude Coding611 topic

Where does Ting‐Zhu Huang work?

Ting‐Zhu Huang's main affiliation in the publication record is University of Electronic Science and Technology of China, China.

How many publications and citations does Ting‐Zhu Huang have?

OpenAlex counts 730 works and 13,374 citations for Ting‐Zhu Huang, an h-index of 58, ranking #569,577 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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