Fruit quality and defect image classification with conditional GAN data augmentation

Jordan J. Bird*, Chloe M. Barnes, Luis J. Manso, Anikó Ekárt, Diego R. Faria

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

Abstract

Contemporary Artificial Intelligence technologies allow for the employment of Computer Vision to discern good crops from bad, providing a step in the pipeline of selecting healthy fruit from undesirable fruit, such as those which are mouldy or damaged. State-of-the-art works in the field report high accuracy results on small datasets (
Original languageEnglish
Article number110684
JournalScientia Horticulturae
Volume293
Early online date1 Nov 2021
DOIs
Publication statusE-pub ahead of print - 1 Nov 2021

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