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Sankore

Named after the University of Sankore in Timbuktu — one of the world’s oldest centres of learning. Every figure here is computed from work-level records in our own graph, never copied from a source’s summary count.

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Coverage is partial and says so. A country appears with its research output only once its works have been swept; until then the portal shows whatever the graph happens to hold for it and labels it as exactly that.

Comparing Machine Learning Algorithms in Land Use Land Cover Classification of Landsat 8 (OLI) Imagery

2022Asian Research Journal of MathematicsJournalOpen access

10.9734/arjom/2022/v18i330367 Full text14 citations

Authors

6 authors.

O. J. AigbokhanFirst author
- Forestry Research Institute of Nigeria (NG)
O. J. Pelemo
- Forestry Research Institute of Nigeria (NG)
O. M. Ogoliegbune
- Forestry Research Institute of Nigeria (NG)
N. E. Essien
- Forestry Research Institute of Nigeria (NG)
A. A. Ekundayo
- Forestry Research Institute of Nigeria (NG)
Shamsuddeen AdamuSenior author
- Forestry Research Institute of Nigeria (NG)
as printed: S. I. Adamu

Fields

Assignment is probabilistic — a work belongs to several fields in proportions.

Remote-Sensing Image Classificationlevel 3 · 0.94

Sources

Several sources describing one work is the point — it means the record rests on more than one authority.

openalexseen September 9, 2026
2022 · Asian Research Journal of Mathematics · 14 citations
https://openalex.org/W4223471442

Comparing Machine Learning Algorithms in Land Use Land Cover Classification of Landsat 8 (OLI) Imagery · Sankore