Science Explorer Back to mapMap
Discussion
Researcher · Superior University · Pakistan

Arslan Akram

Arslan Akram publishes mostly in Computer Vision and Pattern Recognition, Artificial Intelligence and Radiology, Nuclear Medicine and Imaging, on topics such as Digital Media Forensic Detection, Generative Adversarial Networks and Image Synthesis and Advanced Steganography and Watermarking Techniques.

ORCID 0000-0001-9424-1697 OpenAlex
World rank
#818,213
of 7,710,434 ranked researchers
Rank in Pakistan
#2,469
of 32,975
Works
25
Citations
405
Citations per work
16.2
h-index
11
i10-index 11Top 39% in Computer Vision and Pattern Recognition
Arslan Akram

What does Arslan Akram research?

Arslan Akram's work is mostly in Computer Science (46%), Medicine (8%), Neuroscience (6%).

Physical Sciences: 12 works · 46.2% of their workComputer Science: 12 works · 46.2% of their workComputer Vision and Pattern Recognition: 8 works · 32.8% of their workArtificial Intelligence: 3 works · 13.4% of their workEverything else: 9 works · 37.3% of their workLife Sciences: 2 works · 9.0% of their workNeuroscience: 2 works · 6.0% of their workCognitive Neuroscience: 1 works · 3.0% of their workNeurology: 1 works · 3.0% of their workBiochemistry, Genetics and Molecular Biology: 1 works · 3.0% of their workBiophysics: 1 works · 3.0% of their workHealth Sciences: 2 works · 7.5% of their workMedicine: 2 works · 7.5% of their workRadiology, Nuclear Medicine and Imaging: 2 works · 7.5% of their workTHEIR WORKArslan Akram25works
Life Sciences9%Physical Sciences46%Health Sciences8%

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 Science1246.2%
  2. Everything else937.3%
    1. Neuroscience26.0%
    2. Biochemistry, Genetics and Molecular Biology13.0%
    1. Medicine27.5%
  1. 1Computer Vision and Pattern Recognition33% of their works
  2. 2Artificial Intelligence13% of their works
  3. 3Radiology, Nuclear Medicine and Imaging8% of their works
  4. 4Biophysics3% of their works
  5. 5Cognitive Neuroscience3% of their works
  6. 6Neurology3% of their works

Research topics

Which keywords describe Arslan Akram's research?

The keywords of their largest research topics: Deep Learning, Machine Learning, Digital Forensics, Image Forgery Detection, Generative Adversarial Networks, Image Synthesis, Reversible Data Embedding and Steganography.

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.

All 18 words, with their numbers
  1. Deep Learning267 topics
  2. Machine Learning94 topics
  3. Digital Forensics81 topic
  4. Image Forgery Detection81 topic
  5. Generative Adversarial Networks51 topic
  6. Image Synthesis51 topic
  7. Reversible Data Embedding41 topic
  8. Steganography41 topic
  9. Detection31 topic
  10. Hate Speech31 topic
  11. Autism Spectrum Disorders21 topic
  12. Bioimage Analysis21 topic
  13. Brain Tumor21 topic
  14. Genetics21 topic
  15. High-Content Screening21 topic
  16. Histopathology Images21 topic
  17. MRI21 topic
  18. Medical Image Analysis21 topic

Where does Arslan Akram work?

Arslan Akram's main affiliation in the publication record is Superior University, Pakistan.

How many publications and citations does Arslan Akram have?

OpenAlex counts 25 works and 405 citations for Arslan Akram, an h-index of 11, ranking #818,213 of 7,710,434 researchers worldwide on the quality score.

Ranked on field-normalised 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 Arslan Akram. Posts are plain text and can be reported.