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Main Authors: 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
Format: Preprint
Published: 2024
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Online Access:https://arxiv.org/abs/2401.11617
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author 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
author_facet 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
contents 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.
format Preprint
id arxiv_https___arxiv_org_abs_2401_11617
institution arXiv
publishDate 2024
record_format arxiv
spellingShingle The State of Computer Vision Research in Africa
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
Computer Vision and Pattern Recognition
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.
title The State of Computer Vision Research in Africa
topic Computer Vision and Pattern Recognition
url https://arxiv.org/abs/2401.11617