Pre-trained noise based unsupervised GAN for fruit disease classification in imbalanced datasets

• Published in: Pattern analysis and applications : PAA Vol. 28; no. 2
• Main Authors: Gupta, Sachin, Tripathi, Ashish Kumar, Lewis, Nkenyereye
• Format: Journal Article
• Language: English
• Published: London Springer London 01.06.2025; Springer Nature B.V
• Subjects: Agricultural production; Artificial neural networks; Classification; Computer Science; Data augmentation; Datasets; Image quality; Image resolution; Machine learning; Medical imaging; Neural networks; Original Article; Pattern Recognition; Performance enhancement; Performance evaluation; Random noise; Structural integrity; Synthetic data; Deep learning; Eggplant images; Image augmentation; Fruit disease classification; Generative adversarial network

Early disease diagnosis in edible fruits and vegetables is crucial for sustainable economic agricultural production. Recently, deep neural networks have explicitly shown exceptional performance in early disease recognition. However, an insufficient and scarce dataset is a critical issue for training...