Generative Adversarial Networks (GANs) for Image Augmentation in Farming: A Review

Generative Adversarial Networks (GANs) for Image Augmentation in Farming: A Review

Enhancing model performance in agricultural image analysis faces challenges due to limited datasets, biological variability, and uncontrolled environments. Deep learning models require large, realistic datasets, which are often difficult to obtain. Data augmentation, especially through Generative Ad...

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Bibliographic Details
Main Authors: Zahid Ur Rahman, Mohd Shahrimie Mohd Asaari, Haidi Ibrahim, Intan Sorfina Zainal Abidin, Mohamad Khairi Ishak
Format: Article
Language:English
Published: IEEE 2024-01-01
Series:IEEE Access
Subjects:
Image augmentation
synthetic data generation
data scarcity
agriculture analytics
computer vision
deep learning
Online Access:https://ieeexplore.ieee.org/document/10767244/
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