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October 11, 2025Indian Journal of Horticulture0 citations

Explainable AI Framework for Accurate Mango Leaf Disease Detection

The Explainable AI for mango leaf disease detection: bridging the gap between model accuracy and farmers usability

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This research introduces an explainable AI approach using CNN for identifying mango leaf diseases, highlighting model reliability and farmer trust.

The model achieved 92.8% accuracy in classifying seven major mango leaf diseases.
Using the mangoleafbd dataset, the study utilized a modified VGG-16 CNN with Grad-CAM for disease detection.
The explainable AI framework enhances farmer trust by providing graphical explanations of model decisions.
Insights from this research aim to optimize the model for efficiency in low-resource agricultural settings.

Nasar et al. (2025) studied this question.

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October 11, 2025Indian Journal of Horticulture0 citations

The Explainable AI for mango leaf disease detection: bridging the gap between model accuracy and farmers usability

View Full Paper

Ask AI

Bookmark

Authors

This research introduces an explainable AI approach using CNN for identifying mango leaf diseases, highlighting model reliability and farmer trust.

The model achieved 92.8% accuracy in classifying seven major mango leaf diseases.
Using the mangoleafbd dataset, the study utilized a modified VGG-16 CNN with Grad-CAM for disease detection.
The explainable AI framework enhances farmer trust by providing graphical explanations of model decisions.
Insights from this research aim to optimize the model for efficiency in low-resource agricultural settings.

Nasar et al. (2025) studied this question.

View Full Paper

Ask AI

Bookmark