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VotTomNet: Tomato Disease Diagnosis AI by IAES International Journal of Robotics and Automation is a document available to read on EtoBox.

What is VotTomNet: Tomato Disease Diagnosis AI about?

The research introduces VotTomNet, an advanced system for diagnosing tomato leaf diseases using transfer learning and ensemble voting techniques, achieving a remarkable accuracy of 99.2%. By integrating six pre-trained convolutional neural networks and employing both soft and hard voting methods, the model enhances diagnostic precision and offers a practical solution for large-scale agricultural applications. This innovative approach not only improves disease detection rates but also lays the groundwork for

Author

IAES International Journal of Robotics and Automation

Language

EN