Science Explorer Back to mapMap
Discussion
Researcher · Comilla University · Bangladesh

Aditi Sarker

Aditi Sarker publishes mostly in Computer Vision and Pattern Recognition, Artificial Intelligence and Psychiatry and Mental health, on topics such as Image Enhancement Techniques, Sentiment Analysis and Opinion Mining and Image Retrieval and Classification Techniques.

ORCID 0009-0006-5443-8392 OpenAlex
World rank
#5,744,885
of 7,710,434 ranked researchers
Rank in Bangladesh
#10,412
of 14,256
Works
26
Citations
119
Citations per work
4.6
h-index
5
i10-index 5Top 87% in Computer Vision and Pattern Recognition
Aditi Sarker

What does Aditi Sarker research?

Aditi Sarker's work is mostly in Computer Science (30%), Medicine (10%), Engineering (4%).

Everything else: 14 works · 55.7% of their workPhysical Sciences: 9 works · 34.3% of their workComputer Science: 8 works · 30.0% of their workComputer Vision and Pattern Recognition: 5 works · 20.0% of their workArtificial Intelligence: 1 works · 5.7% of their workInformation Systems: 1 works · 4.3% of their workEngineering: 1 works · 4.3% of their workMedia Technology: 1 works · 4.3% of their workHealth Sciences: 3 works · 10.0% of their workMedicine: 3 works · 10.0% of their workPsychiatry and Mental health: 1 works · 5.7% of their workEpidemiology: 1 works · 4.3% of their workTHEIR WORKAditi Sarker26works
Physical Sciences34%Health Sciences10%

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. Everything else1455.7%
    1. Computer Science830.0%
    2. Engineering14.3%
    1. Medicine310.0%
  1. 1Computer Vision and Pattern Recognition20% of their works
  2. 2Artificial Intelligence6% of their works
  3. 3Psychiatry and Mental health6% of their works
  4. 4Information Systems4% of their works
  5. 5Media Technology4% of their works
  6. 6Epidemiology4% of their works

Research topics

Which keywords describe Aditi Sarker's research?

The keywords of their largest research topics: Deep Learning, Convolutional Neural Networks, Machine Learning, Contrast Enhancement, Dehazing, Content-Based Image Retrieval, COVID-19 and Handwriting Recognition.

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 Learning73 topics
  2. Convolutional Neural Networks42 topics
  3. Machine Learning42 topics
  4. Contrast Enhancement31 topic
  5. Dehazing31 topic
  6. COVID-1921 topic
  7. Content-Based Image Retrieval21 topic
  8. Handwriting Recognition21 topic
  9. Medical Imaging21 topic
  10. Opinion Mining21 topic
  11. Sentiment Analysis21 topic
  12. Shape Matching21 topic
  13. Text Detection21 topic
  14. Crohn's Disease11 topic
  15. Genetic Adaptation11 topic
  16. Gut Microbiota11 topic
  17. Inflammatory Bowel Disease11 topic
  18. Lactase Persistence11 topic
  19. Microbial Communities11 topic

Where does Aditi Sarker work?

Aditi Sarker's main affiliation in the publication record is Comilla University, Bangladesh.

How many publications and citations does Aditi Sarker have?

OpenAlex counts 26 works and 119 citations for Aditi Sarker, an h-index of 5, ranking #5,744,885 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 Aditi Sarker. 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.