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Researcher · Sejong University · South Korea

Yeong Hyeon Gu

Yeong Hyeon Gu publishes mostly in Artificial Intelligence, Computer Vision and Pattern Recognition and Plant Science, on topics such as Advanced Neural Network Applications, Smart Agriculture and AI and Advanced Text Analysis Techniques.

ORCID 0000-0002-0002-9386 OpenAlex
World rank
#186,548
of 7,710,434 ranked researchers
Rank in South Korea
#1,076
of 162,609
Works
130
Citations
1.6k
Citations per work
12.0
h-index
19
i10-index 38Top 14% in Artificial Intelligence
Yeong Hyeon Gu

What does Yeong Hyeon Gu research?

Yeong Hyeon Gu's work is mostly in Computer Science (42%), Agricultural and Biological Sciences (8%), Engineering (4%).

Physical Sciences: 59 works · 45.2% of their workComputer Science: 54 works · 41.6% of their workArtificial Intelligence: 25 works · 18.9% of their workComputer Vision and Pattern Recognition: 21 works · 15.8% of their workInformation Systems: 9 works · 6.9% of their workEngineering: 5 works · 3.6% of their workBiomedical Engineering: 5 works · 3.6% of their workEverything else: 58 works · 44.8% of their workLife Sciences: 10 works · 7.8% of their workAgricultural and Biological Sciences: 10 works · 7.8% of their workPlant Science: 10 works · 7.8% of their workHealth Sciences: 3 works · 2.2% of their workMedicine: 3 works · 2.2% of their workRadiology, Nuclear Medicine and Imaging: 3 works · 2.2% of their workTHEIR WORKYeong Hyeon Gu130works
Life Sciences8%Physical Sciences45%Health Sciences2%

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 Science5441.6%
    2. Engineering53.6%
  2. Everything else5844.8%
    1. Agricultural and Biological Sciences107.8%
    1. Medicine32.2%
  1. 1Artificial Intelligence19% of their works
  2. 2Computer Vision and Pattern Recognition16% of their works
  3. 3Plant Science8% of their works
  4. 4Information Systems7% of their works
  5. 5Biomedical Engineering4% of their works
  6. 6Radiology, Nuclear Medicine and Imaging2% of their works

Research topics

Which keywords describe Yeong Hyeon Gu's research?

The keywords of their largest research topics: Deep Learning, Machine Learning, Neural Networks, Convolutional Neural Networks, Image Recognition, Plant Disease Detection, Smart Farming and Automatic.

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. Deep Learning596 topics
  2. Machine Learning283 topics
  3. Neural Networks212 topics
  4. Convolutional Neural Networks161 topic
  5. Image Recognition161 topic
  6. Plant Disease Detection151 topic
  7. Smart Farming151 topic
  8. Automatic111 topic
  9. Extraction111 topic
  10. Machine Translation101 topic
  11. Word Representation101 topic
  12. Feature Matching81 topic
  13. Local Descriptors81 topic
  14. Opinion Mining71 topic
  15. Sentiment Analysis71 topic
  16. Spine Segmentation71 topic
  17. Vertebrae Detection71 topic
  18. Brain Tumor61 topic
  19. MRI61 topic

Where does Yeong Hyeon Gu work?

Yeong Hyeon Gu's main affiliation in the publication record is Sejong University, South Korea.

How many publications and citations does Yeong Hyeon Gu have?

OpenAlex counts 130 works and 1,559 citations for Yeong Hyeon Gu, an h-index of 19, ranking #186,548 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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