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Researcher · Amazon (United States) · United States

Feng-Ju Chang

Feng-Ju Chang publishes mostly in Artificial Intelligence, Computer Vision and Pattern Recognition and Signal Processing, on topics such as Speech Recognition and Synthesis, Speech and Audio Processing and Music and Audio Processing.

ORCID 0000-0003-2405-3118 OpenAlex
World rank
#2,035,193
of 7,710,434 ranked researchers
Rank in United States
#616,600
of 1,627,098
Works
50
Citations
768
Citations per work
15.4
h-index
13
i10-index 14Top 28% in Artificial Intelligence
Feng-Ju Chang

What does Feng-Ju Chang research?

Feng-Ju Chang's work is mostly in Computer Science (76%), Social Sciences (4%), Neuroscience (2%).

Physical Sciences: 39 works · 78.6% of their workComputer Science: 38 works · 76.5% of their workArtificial Intelligence: 17 works · 34.0% of their workComputer Vision and Pattern Recognition: 12 works · 24.1% of their workSignal Processing: 9 works · 18.4% of their workPhysics and Astronomy: 1 works · 2.1% of their workAtomic and Molecular Physics, and Optics: 1 works · 2.1% of their workEverything else: 8 works · 15.8% of their workSocial Sciences: 2 works · 3.5% of their workSocial Sciences: 2 works · 3.5% of their workSociology and Political Science: 2 works · 3.5% of their workLife Sciences: 1 works · 2.1% of their workNeuroscience: 1 works · 2.1% of their workCognitive Neuroscience: 1 works · 2.1% of their workTHEIR WORKFeng-Ju Chang50works
Life Sciences2%Physical Sciences79%Social Sciences4%

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 Science3876.5%
    2. Physics and Astronomy12.1%
  2. Everything else815.8%
    1. Social Sciences23.5%
    1. Neuroscience12.1%
  1. 1Artificial Intelligence34% of their works
  2. 2Computer Vision and Pattern Recognition24% of their works
  3. 3Signal Processing18% of their works
  4. 4Sociology and Political Science4% of their works
  5. 5Cognitive Neuroscience2% of their works
  6. 6Atomic and Molecular Physics, and Optics2% of their works

Research topics

Which keywords describe Feng-Ju Chang's research?

The keywords of their largest research topics: Convolutional Neural Networks, Deep Learning, Neural Networks, Acoustic Modeling, Deep Neural Networks, Face Recognition, Audio-Visual Speech Recognition and Speech Enhancement.

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. Convolutional Neural Networks413 topics
  2. Deep Learning333 topics
  3. Neural Networks222 topics
  4. Acoustic Modeling201 topic
  5. Deep Neural Networks201 topic
  6. Face Recognition162 topics
  7. Audio-Visual Speech Recognition121 topic
  8. Speech Enhancement121 topic
  9. Audio Signal Classification111 topic
  10. Music Information Retrieval111 topic
  11. Age Estimation101 topic
  12. Facial Landmark Detection101 topic
  13. Machine Translation101 topic
  14. Word Representation101 topic
  15. Dimensionality Reduction61 topic
  16. Feature Selection61 topic
  17. Neural Machine Translation61 topic
  18. Statistical Machine Translation61 topic
  19. Markov Decision Processes51 topic
  20. Spoken Dialogue Systems51 topic

Where does Feng-Ju Chang work?

Feng-Ju Chang's main affiliation in the publication record is Amazon (United States), United States.

How many publications and citations does Feng-Ju Chang have?

OpenAlex counts 50 works and 768 citations for Feng-Ju Chang, an h-index of 13, ranking #2,035,193 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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