http://opendata.unex.es/recurso/ciencia-tecnologia/investigacion/publicaciones/Publicacion/2022-116
Literals
- vivo:identifier
- ou:eid
- dcterms:contributor
- Bird J.J., Barnes C.M., Manso L.J., Ekart A., Faria D.R.
- ou:bibtex
- @article{0de7fec0032e4586ab05ecf244ba97ef,
title = 'Fruit quality and defect image classification with conditional GAN data augmentation',
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 (',
author = 'Bird, {Jordan J.} and Barnes, {Chloe M.} and Manso, {Luis J.} and Anik{\'o} Ek{\'a}rt and Faria, {Diego R.}',
year = '2022',
month = feb,
day = '5',
doi = '10.1016/j.scienta.2021.110684',
language = 'English',
volume = '293',
journal = 'Scientia Horticulturae',
issn = '0304-4238',
publisher = 'Elsevier',
}
- bibo:doi
- 10.1016/j.scienta.2021.110684
- dcterms:creator
- fabio:hasPublicationYear
- bibo:issn
- dcterms:publisher
- ou:tipoPublicacion
- dcterms:title
- Fruit quality and defect image classification with conditional GAN data augmentation
- vcard:url
- ou:urlOrcid
- ou:urlScopus
- ou:vecesCitado
- bibo:volume