Author

Dedi Setiadi

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Open access Jul 2026

Improving the Performance of Convolutional Neural Networks (CNN) in Identification of Agricultural Plant Diseases

The findings confirm that the Inception V3 architecture provides a robust and efficient solution for automating plant disease diagnosis in the field and demonstrates that computational efficiency can go hand in hand with accuracy improvements on complex agricultural image datasets.

Dedi Setiadi, Fido Rizki · SMATIKA JURNAL · 0 citations