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Researcher · Drexel University · United States

Matthew Christopher Stamm

Matthew Christopher Stamm publishes mostly in Computer Vision and Pattern Recognition, Artificial Intelligence and Law, on topics such as Digital Media Forensic Detection, Advanced Steganography and Watermarking Techniques and Generative Adversarial Networks and Image Synthesis.

ORCID 0000-0002-3986-4039 OpenAlex
World rank
#149,854
of 7,710,434 ranked researchers
Rank in United States
#56,500
of 1,627,098
Works
115
Citations
4.8k
Citations per work
42.1
h-index
30
i10-index 48Top 5.1% in Computer Vision and Pattern Recognition
Matthew Christopher Stamm

What does Matthew Christopher Stamm research?

Matthew Christopher Stamm's work is mostly in Computer Science (80%), Social Sciences (6%), Engineering (4%).

Physical Sciences: 96 works · 83.3% of their workComputer Science: 92 works · 79.6% of their workComputer Vision and Pattern Recognition: 66 works · 57.0% of their workArtificial Intelligence: 16 works · 13.7% of their workSignal Processing: 6 works · 5.2% of their workInformation Systems: 4 works · 3.7% of their workEngineering: 4 works · 3.7% of their workMedia Technology: 4 works · 3.7% of their workEverything else: 13 works · 11.2% of their workSocial Sciences: 6 works · 5.5% of their workSocial Sciences: 6 works · 5.5% of their workLaw: 6 works · 5.5% of their workTHEIR WORKMatthewChristopher Stamm115works
Physical Sciences83%Social Sciences6%

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 Science9279.6%
    2. Engineering43.7%
  2. Everything else1311.2%
    1. Social Sciences65.5%
  1. 1Computer Vision and Pattern Recognition57% of their works
  2. 2Artificial Intelligence14% of their works
  3. 3Law6% of their works
  4. 4Signal Processing5% of their works
  5. 5Media Technology4% of their works
  6. 6Information Systems4% of their works

Research topics

Which keywords describe Matthew Christopher Stamm's research?

The keywords of their largest research topics: Deep Learning, Digital Forensics, Copy-Move Forgery, Image Forgery Detection, Neural Networks, Reversible Data Embedding, Steganography and Security.

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. Deep Learning2055 topics
  2. Digital Forensics1002 topics
  3. Copy-Move Forgery881 topic
  4. Image Forgery Detection881 topic
  5. Neural Networks804 topics
  6. Reversible Data Embedding491 topic
  7. Steganography491 topic
  8. Security342 topics
  9. Generative Adversarial Networks311 topic
  10. Image Synthesis311 topic
  11. Adversarial Examples221 topic
  12. Robustness221 topic
  13. Legal Semiotics181 topic
  14. Visual Jurisprudence181 topic
  15. Anomaly Detection151 topic
  16. Unsupervised151 topic
  17. Autofocusing121 topic
  18. Cloud Computing121 topic
  19. Depth Estimation121 topic
  20. Internet of Things121 topic

Where does Matthew Christopher Stamm work?

Matthew Christopher Stamm's main affiliation in the publication record is Drexel University, United States.

How many publications and citations does Matthew Christopher Stamm have?

OpenAlex counts 115 works and 4,836 citations for Matthew Christopher Stamm, an h-index of 30, ranking #149,854 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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