Localized Data Work as a Precondition for Data-Centric ML: A Case Study of Full Lifecycle Crop Disease Identification in Ghana

Localized Data Work as a Precondition for Data-Centric ML: A Case Study of Full Lifecycle Crop Disease Identification in Ghana

The Ghana Cashew Disease Identification with Artificial Intelligence (CADI AI) project demonstrates the importance of sound data work as a precondition for the delivery of useful, localized datacentric solutions for public good tasks such as agricultural productivity and food security. Drone collect...

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Veröffentlicht in:arXiv.org 2023-07
Hauptverfasser: Darlington Akogo, Samori, Issah, Akafia, Cyril, Fiagbor, Harriet, Andrews Kangah, Asiedu, Donald Kwame, Fuachie, Kwabena, Oala, Luis
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Artificial intelligence
Data collection
Machine learning
Plant diseases
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container_title arXiv.org
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creator Darlington Akogo
Samori, Issah
Akafia, Cyril
Fiagbor, Harriet
Andrews Kangah
Asiedu, Donald Kwame
Fuachie, Kwabena
Oala, Luis
description The Ghana Cashew Disease Identification with Artificial Intelligence (CADI AI) project demonstrates the importance of sound data work as a precondition for the delivery of useful, localized datacentric solutions for public good tasks such as agricultural productivity and food security. Drone collected data and machine learning are utilized to determine crop stressors. Data, model and the final app are developed jointly and made available to local farmers via a desktop application.
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subjects Artificial intelligence
Data collection
Machine learning
Plant diseases
title Localized Data Work as a Precondition for Data-Centric ML: A Case Study of Full Lifecycle Crop Disease Identification in Ghana
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