Systematic Literature Review of Deep Learning models for Computer Vision Applications: Deployment Challenges in Nigeria

dc.contributor.authorAbdullahi, I. M., Siyaka, H.O., Alhaji, G.S., Maliki, D., Dauda
dc.date.accessioned2025-05-04T16:53:50Z
dc.date.issued2023-09-05
dc.descriptionThis paper presents a comprehensive review of recent deep learning models applied to computer vision, emphasizing the transformative impact of deep learning in fields such as image recognition, natural language processing, and speech recognition. While acknowledging the rapid global advancement of these technologies, the paper focuses on the unique challenges faced by developing countries—specifically Nigeria—in adopting deep learning solutions. These challenges include manual data collection, insufficient cloud storage infrastructure, unreliable power and internet services, and inadequate funding for technological development. Unlike previous reviews, this work specifically addresses Nigeria’s barriers to deep learning adoption and offers practical recommendations, such as developing local cloud services, improving infrastructure, and increasing government investment in the IT sector to foster innovation and support local experts.
dc.description.abstractDeep learning has gained attention recently. Since its adoption, deep learning has provided state-of-the-art solutions to lots of standing computational problems. One of the areas it has gained unequaled success is computer vision. The success of deep learning is not limited to computer vision only, it has also recorded unmatchable success in areas like natural language processing and speech recognition. With the advent of big data, the use and importance of deep learning can only continue to grow. One downside of this algorithm is its computational requirements: large datasets and high-end computing devices. In this paper, we provide an overview of recent deep learning models for computer vision, and we also highlighted the challenges faced by developing countries in adopting these technologies. No review has covered the challenges faced by Nigeria in deploying this technology. Some of the challenges highlighted include manual data collection and lack of adequate cloud storage services. Inadequate infrastructures such as power and network facilities, and finally, lack of adequate funding of the sector. It was recommended that local cloud services be established to encourage local data storage and reduce storage cost. Also, adequate investment for power and network availability should be made. Finally, there should be enough budget allocation to IT sector that will encourage technocrat and experts to develop and fully harness the benefit of the technology.
dc.identifier.citationAbdullahi, I. M., Siyaka, H.O., Alhaji, G.S., Maliki, D., Dauda, A.I. (2023). Systematic Literature Review of Deep Learning models for Computer Vision Applications: Deployment Challenges in Nigeria. Journal of Science Technology and Education (JOSTE), 11(3). Pp 286-297. available at: www.atbuftejoste.com
dc.identifier.urihttp://repository.futminna.edu.ng:4000/handle/123456789/1803
dc.language.isoen
dc.publisherJOURNAL OF SCIENCE TECHNOLOGY AND EDUCATION
dc.titleSystematic Literature Review of Deep Learning models for Computer Vision Applications: Deployment Challenges in Nigeria
dc.typeArticle

Files

Original bundle

Now showing 1 - 1 of 1
No Thumbnail Available
Name:
ATBU IBRAHIM 1908-3663-1-PB.pdf
Size:
1.31 MB
Format:
Adobe Portable Document Format

License bundle

Now showing 1 - 1 of 1
No Thumbnail Available
Name:
license.txt
Size:
1.71 KB
Format:
Item-specific license agreed to upon submission
Description: