Optimizing Rice Plant Disease Classification Using Data Augmentation with GANs on Convolutional Neural Networks

Optimizing Rice Plant Disease Classification Using Data Augmentation with GANs on Convolutional Neural Networks

Background: Rice disease classification using CNN models faces challenges due to limited data, particularly in minority classes, and inconsistent image quality, which affect model performance. Data augmentation techniques can potentially enhance classification accuracy by improving data diversity a...

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Bibliographic Details
Main Authors: Tinuk Agustin, Indrawan Ady Saputro, Mochammad Luthfi Rahmadi
Format: Article
Language:English
Published: Universitas Nusantara PGRI Kediri 2025-02-01
Series:Intensif: Jurnal Ilmiah Penelitian Teknologi dan Penerapan Sistem Informasi
Subjects:
CNN
DCGAN
Image Quality Enhancement
Imbalanced Datasets
Synthetic Data
Online Access:https://ojs.unpkediri.ac.id/index.php/intensif/article/view/23834
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