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What is Automated Rice Grain Classification Using CNNs about?

This study presents an automated rice grain classification framework using transfer learning with convolutional neural networks (CNNs) to enhance grading accuracy and efficiency. The GrainSpace dataset, containing 79,200 images across eight rice subtypes, was analyzed using five pre-trained models, with EfficientNet-B0 achieving the highest accuracy of 99.51%. The research highlights the effectiveness of transfer learning in agricultural automation, providing a reliable and explainable solution for rice gra

Author

Dharmendra Prajapati

Language

EN