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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.

Modified Deep Learning Model for Efficient Recyclable Waste Classification: A Comparative Study of Convolutional Network Architectures

2025European Journal of Engineering Science and TechnologyJournalOpen access

10.33422/ejest.v8i2.1586 Full text0 citations

Authors

3 authors across 3 institutions in 1 country.

Tamuno-Omie J AlaliboFirst author
- Rivers State University (NG)
Nkolika Nwazor
- University of Port Harcourt (NG)
as printed: Nkolika O Nwazor
L.I. OborkhaleSenior author
- Michael Okpara University of Agriculture (NG)
as printed: Lawrence Oborkhale

Fields

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

Municipal Solid Waste Managementlevel 3 · 0.59
Advanced Neural Network Applicationslevel 3 · 0.07
Internet of Things and AIlevel 3 · 0.02

Sources

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

openalexseen September 9, 2026
2025 · European Journal of Engineering Science and Technology · 0 citations
https://openalex.org/W7128383205

Modified Deep Learning Model for Efficient Recyclable Waste Classification: A Comparative Study of Convolutional Network Architectures · Sankore