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September 27, 2025Vinh University Journal of Science

Using Convolutional Neural Network to Diagnose Diseases on Mango Leaves

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Authors

VTVO Tan ToanNTNGUYEN Duc Thinh

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Overview

Deep learning methods improved disease detection accuracy in mango leaves, highlighting enhanced agricultural management.

Key Points

  • The model achieved an accuracy of over 97.60% in classifying mango leaf diseases, showcasing its precision.
  • A dataset of 4,800 images was utilized, providing robust training and testing for identifying seven diseases.
  • A convolutional neural network was developed to analyze mango leaf imagery for effective disease diagnosis.
  • This method may enable improved crop yields and reduced reliance on chemical treatments for mango diseases.

Cite This Study

Toan et al. (2025) studied this question.

synapsesocial.com/papers/68d7be70eebfec0fc523859ahttps://doi.org/10.56824/vujs.2025a064a
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Also Consider

Synapse has enriched 5 closely related papers on similar clinical questions. Consider them for comparative context:

  1. 1Deep Learning-Based Detection of Mango Leaf Diseases Using Convolutional Neural Networks2026
  2. 2Deep Learning for Detection of Mango Leaf Disease: A Comparative Study Using Convolutional Neural Networks Models2024 · 14 citations
  3. 3Development of a Robust CNN Model for Mango Leaf Disease Detection and Classification: A Precision Agriculture Approach2024 · 29 citations
  4. 4Synergistic Use of Convolutional Neural Networks and Support Vector Machines for Mango Leaf Disease Diagnosis2025
  5. 5The Explainable AI for mango leaf disease detection: bridging the gap between model accuracy and farmers usability2025 · 2 citations