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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.

Michael Wilson · Sankore

Kwame Nkrumah University of Science and Technology

Michael Wilson

ORCID, self-asserted

ORCID 0000-0002-9657-6068

This profile carries an ORCID the researcher published on their own record — the strongest evidence available short of a human confirming it.

Publications

5

Citations

24

h-index

2

Computed over the works the graph holds, so it is a floor rather than a career figure.

i10-index

1

Works published 2022 onward have been swept for this country. Figures are complete within that window, to the extent the open indexes are.

Affiliations

Every institution this scholar has appeared with on a work, by how many.

Institute for Scientific and Technological Information6 works
Council for Scientific and Industrial Research6 works
Kwame Nkrumah University of Science and Technology2 works

Publications

5 works in the graph, newest first.

Enabling Intelligence on the Edge: Leveraging Edge Impulse to Deploy Multiple Deep Learning Models on Edge Devices for Tomato Leaf Disease Detection
2024AgriEngineeringJournalOpen access17 citations10.3390/agriengineering6040203
TinyML Implementation on Microcontrollers: The Case of Maize Leaf Disease Identification
2024PublicationOpen access5 citations10.1109/ictas59620.2024.10507115
Power Efficient Non-Mechanical Weather Station: Harnessing TinyML for Rainfall Classification and Environmental Sensing
2024Publication1 citations10.1109/icast61769.2024.10856468
A Review of Computational Load-Balancing for Mobile Edge Computing
2023Lecture notes in networks and systemsPublicationFirst authorCorresponding1 citations10.1007/978-3-031-37717-4_7
The Efficiency of Convolution on Gemmini Deep Learning Hardware Accelerator

2023PublicationOpen access0 citations10.1109/africon55910.2023.10293709