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All Journal International Journal of Informatics Engineering and Computing
Fan Hao Yi
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Computer Science & IT

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Stepping up Onion Classification Model using CNN Algorithm Fan Hao Yi; Moh. K. Syed
International Journal of Informatics Engineering and Computing Vol. 1 No. 2 (2024): International Journal of Informatics Engineering and Computing
Publisher : ASTEEC

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70687/ijimatic.v1.i2.47

Abstract

Traditional shallot classification methods, relying on visual inspection or conventional image processing, face limitations in dataset identification. To address the issues, we propose a CNN model for classifying shallot types. The study involves collecting a large dataset, preprocessing, and training the model with optimized parameters to maximize accuracy. By adjusting hyperparameters, we achieve a balance between accuracy and performance time. With 50 epochs and a batch size of 64, the model achieves over 80% accuracy in classification tests. These results demonstrate the effectiveness of CNN in shallot classification, outperforming traditional methods. Future work could explore advanced architectures like Generative Adversarial Networks (GAN) and Graph Convolutional Networks (GCN) to further enhance the model's performance.
Co-Authors Moh. K. Syed