CitrusUAT: A dataset of orange Citrus sinensis leaves for abnormality detection using image analysis techniques.
Data Brief
; 52: 109908, 2024 Feb.
Article
em En
| MEDLINE
| ID: mdl-38093853
ABSTRACT
Around the world, citrus production and quality are threatened by diseases caused by fungi, bacteria, and viruses. Citrus growers are currently demanding technological solutions to reduce the economic losses caused by citrus diseases. In this context, image analysis techniques have been widely used to detect citrus diseases, extracting discriminant features from an input image to distinguish between healthy and abnormal cases. The dataset presented in this article is helpful for training, validating, and comparing citrus abnormality detection algorithms. The data collection comprises 953 color images taken from the orange leaves of Citrus sinensis (L.) Osbeck species. There are 12 nutritional deficiencies and diseases supporting the development of automatic detection methods that can reduce economic losses in citrus production.
Texto completo:
1
Coleções:
01-internacional
Base de dados:
MEDLINE
Idioma:
En
Revista:
Data Brief
Ano de publicação:
2024
Tipo de documento:
Article
País de afiliação:
México
País de publicação:
Holanda