The State of Computer Vision Research in Africa

Autor: Omotayo, Abdul-Hakeem, Mbilinyi, Ashery, Ismaila, Lukman, Turki, Houcemeddine, Abdien, Mahmoud, Gamal, Karim, Tondji, Idriss, Pimi, Yvan, Etori, Naome A., Matar, Marwa M., Broni-Bediako, Clifford, Oppong, Abigail, Gamal, Mai, Ehab, Eman, Dovonon, Gbetondji, Akinjobi, Zainab, Ajisafe, Daniel, Adegboro, Oluwabukola G., Siam, Mennatullah
Rok vydání: 2024
Předmět:
Zdroj: JAIR 2024
Druh dokumentu: Working Paper
DOI: 10.1613/jair.1.16653
Popis: Despite significant efforts to democratize artificial intelligence (AI), computer vision which is a sub-field of AI, still lags in Africa. A significant factor to this, is the limited access to computing resources, datasets, and collaborations. As a result, Africa's contribution to top-tier publications in this field has only been 0.06% over the past decade. Towards improving the computer vision field and making it more accessible and inclusive, this study analyzes 63,000 Scopus-indexed computer vision publications from Africa. We utilize large language models to automatically parse their abstracts, to identify and categorize topics and datasets. This resulted in listing more than 100 African datasets. Our objective is to provide a comprehensive taxonomy of dataset categories to facilitate better understanding and utilization of these resources. We also analyze collaboration trends of researchers within and outside the continent. Additionally, we conduct a large-scale questionnaire among African computer vision researchers to identify the structural barriers they believe require urgent attention. In conclusion, our study offers a comprehensive overview of the current state of computer vision research in Africa, to empower marginalized communities to participate in the design and development of computer vision systems.
Comment: Community Work of Ro'ya Grassroots, https://ro-ya-cv4africa.github.io/homepage/. Published in JAIR,. arXiv admin note: text overlap with arXiv:2305.06773
Databáze: arXiv
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