Countries
Institutions
Fields
Rankings
Compare

Search institutions, scholars, countries and publications

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.

Built from

OpenAlex — works, authorships, subject classification
ROR — institutional identity
ORCID — researcher identity
Crossref — publisher confirmation

Browse

Countries
Institutions
Fields
Rankings
What we cover

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.

Enhanced convolutional neural network methodology for solid waste classification utilizing data augmentation techniques

2024Waste Management BulletinJournalOpen access

10.1016/j.wmb.2024.11.002 Full text15 citations

Authors

3 authors across 3 institutions in 1 country.

D. H. ItamFirst author
- University of Cross River State (NG)
as printed: Daniel Hogan Itam
Ekwueme Chimeme Martin
- University of Cross River State (NG)
Ibiba Taiwo HorsfallSenior authorCorresponding
- Michael Okpara University of Agriculture (NG)
- Rivers State University (NG)

Fields

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

Smart Agriculture and AIlevel 3 · 0.97
Remote-Sensing Image Classificationlevel 3 · 0.97
Internet of Things and AIlevel 3 · 0.97

Sources

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

openalexseen September 9, 2026
2024 · Waste Management Bulletin · 15 citations
https://openalex.org/W4404407121

Enhanced convolutional neural network methodology for solid waste classification utilizing data augmentation techniques · Sankore