Ousmane Dia

462 citations
5 papers · 109 · h-index 3

Impact in

    • Domain Adaptation and Few-Shot Learning
    • Adversarial Robustness in Machine Learning
    • Anomaly Detection Techniques and Applications
    • Machine Learning and Data Classification
    • Reinforcement Learning in Robotics

Papers in

    • Anomaly Detection Techniques and Applications 2
    • Adversarial Robustness in Machine Learning 2
    • Neural Networks and Applications 1
    • Machine Learning and Data Classification 1
    • Vaccine Coverage and Hesitancy 1

Ousmane Dia

5 papers receiving 98 citations

Peers

Ousmane Dia
Comparison fields: 5 of 41
  • Artificial Intelligence 89
  • Acoustics and Ultrasonics 2
  • Computer Vision and Pattern Recognition 41
  • Signal Processing 9
  • Health 5
Replace Francesco Visin with:
Francesco Visin United Kingdom
Jake Snell Canada
Jaesik Yoon Netherlands
Amit Alfassy Israel
Orestis Plevrakis United States
Vihari Piratla India
Amjad Almahairi United States
Shiv Shankar India
Gabriel Pereyra United States
Ousmane Dia relative to Francesco Visin United Kingdom Francesco Visin's profile →
Citations per field
00.5×1.5×1.8×
Francesco Visin · 1×
Citations per year

Countries citing papers authored by Ousmane Dia

Since Specialization
Citations

This map shows the geographic impact of Ousmane Dia's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Ousmane Dia with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Ousmane Dia more than expected).

Fields of papers citing papers by Ousmane Dia

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Ousmane Dia. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Ousmane Dia. The network helps show where Ousmane Dia may publish in the future.

Co-authors

The 24 scholars most cited alongside Ousmane Dia, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Ousmane Dia Line = papers co-authored together Ousmane Dia links everyone, so they are left out of the graph.

All Works

5 of 5 papers shown

About Ousmane Dia

Ousmane Dia is a scholar working on Artificial Intelligence, Health, Computer Vision and Pattern Recognition, Finance and Epidemiology, having authored 5 papers that have together received 109 indexed citations. Recurring topics across this work include Anomaly Detection Techniques and Applications (2 papers), Adversarial Robustness in Machine Learning (2 papers), Vaccine Coverage and Hesitancy (1 paper), Digital Media Forensic Detection (1 paper), HIV, Drug Use, Sexual Risk (1 paper), Healthcare Systems and Reforms (1 paper), Neural Networks and Applications (1 paper) and Machine Learning and Data Classification (1 paper). The work is most often cited by research in Artificial Intelligence (89 citations), Acoustics and Ultrasonics (2 citations), Computer Vision and Pattern Recognition (41 citations), Signal Processing (9 citations) and Health (5 citations). Ousmane Dia has collaborated with scholars based in United States, Switzerland and Japan. Frequent co-authors include Jaesik Yoon, Yoshua Bengio, Taesup Kim, Sungjin Ahn, Sungwoong Kim, Anqi Xu, Archy O. de Berker, Nina Schwalbe, Peter M. Hansen and David J. Pyle. Their work appears in journals such as PLoS ONE and arXiv (Cornell University).

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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