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Machine Learning Models for Fungal Disease Classification in Field Conditions

Agriculture

Crop Disease Detection & Diagnostic Methods

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Agriculture › Crop Disease Detection & Diagnostic Methods

Machine Learning Models for Fungal Disease Classification in Field Conditions

This research develops and validates convolutional neural networks and ensemble machine learning approaches to classify fungal diseases using field-collected image datasets under variable lighting and environmental conditions. The scientific contribution establishes robust computational frameworks that improve classification accuracy while reducing reliance on controlled laboratory settings.

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