Science Explorer Back to mapMap
Discussion
Researcher · National Quemoy University · Taiwan

Tung‐Ching Su

Tung‐Ching Su publishes mostly in Civil and Structural Engineering, Computer Vision and Pattern Recognition and Environmental Engineering, on topics such as Infrastructure Maintenance and Monitoring, Industrial Vision Systems and Defect Detection and Water Systems and Optimization.

ORCID 0009-0004-3781-5227 OpenAlex
World rank
#1,147,196
of 7,710,434 ranked researchers
Rank in Taiwan
#5,737
of 57,035
Works
46
Citations
1k
Citations per work
21.9
h-index
16
i10-index 22Top 21% in Civil and Structural Engineering
Tung‐Ching Su

What does Tung‐Ching Su research?

Tung‐Ching Su's work is mostly in Engineering (34%), Computer Science (14%), Environmental Science (7%).

Physical Sciences: 25 works · 54.9% of their workEngineering: 16 works · 34.3% of their workCivil and Structural Engineering: 11 works · 22.9% of their workIndustrial and Manufacturing Engineering: 3 works · 6.1% of their workMedia Technology: 2 works · 5.3% of their workComputer Science: 6 works · 13.7% of their workComputer Vision and Pattern Recognition: 4 works · 8.4% of their workArtificial Intelligence: 2 works · 5.3% of their workEnvironmental Science: 3 works · 6.9% of their workEnvironmental Engineering: 3 works · 6.9% of their workEverything else: 21 works · 45.1% of their workTHEIR WORKTung‐Ching Su46works
Physical Sciences55%

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. Engineering1634.3%
    2. Computer Science613.7%
    3. Environmental Science36.9%
  2. Everything else2145.1%
  1. 1Civil and Structural Engineering23% of their works
  2. 2Computer Vision and Pattern Recognition8% of their works
  3. 3Environmental Engineering7% of their works
  4. 4Industrial and Manufacturing Engineering6% of their works
  5. 5Artificial Intelligence5% of their works
  6. 6Media Technology5% of their works

Research topics

Which keywords describe Tung‐Ching Su's research?

The keywords of their largest research topics: Deep Learning, Crack Detection, Pavement, Remote Sensing, Fabric Defect Detection, Machine Vision, Leak Detection and Water Distribution Networks.

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 18 words, with their numbers
  1. Deep Learning283 topics
  2. Crack Detection161 topic
  3. Pavement161 topic
  4. Remote Sensing133 topics
  5. Fabric Defect Detection71 topic
  6. Machine Vision71 topic
  7. Leak Detection61 topic
  8. Water Distribution Networks61 topic
  9. Hyperspectral51 topic
  10. Image Analysis51 topic
  11. Phenology51 topic
  12. Sustainable Drainage Systems51 topic
  13. Urban Stormwater Management51 topic
  14. Vegetation Monitoring51 topic
  15. Hough Transform31 topic
  16. Line Detection31 topic
  17. Photogrammetry31 topic
  18. UAV31 topic

Where does Tung‐Ching Su work?

Tung‐Ching Su's main affiliation in the publication record is National Quemoy University, Taiwan.

How many publications and citations does Tung‐Ching Su have?

OpenAlex counts 46 works and 1,007 citations for Tung‐Ching Su, an h-index of 16, ranking #1,147,196 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

Ask a question or share a note about Tung‐Ching Su. Keep it to the research: no personal attacks, advertising or links. Any reader can report a post, which collapses it for everyone until it is opened.