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October 1, 2025International Journal for Research in Applied Science and Engineering TechnologyOpen Access

Crop Disease Prediction Using Deep Learning Algorithm - A Review

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Authors

SSShivangam SoniShoolini University

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Overview

This review finds deep learning enhances crop disease detection accuracy, indicating a shift towards precision agriculture.

Key Points

  • Deep learning methods improve accuracy in crop disease detection, reducing economic losses in agriculture.
  • Convolutional Neural Networks have shown to achieve high accuracy in identifying plant diseases through images.
  • Challenges like data scarcity and computational limits persist, highlighting a need for diverse datasets in the field.
  • Integrating deep learning into agriculture may lead to reduced crop losses, substantially enhancing food security.

Cite This Study

Shivangam Soni (2025) studied this question.

synapsesocial.com/papers/68dd953bfe798ba2fc49993ehttps://doi.org/10.22214/ijraset.2025.74391
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Also Consider

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

  1. 1Machine Learning Framework for Early Detection of Crop Disease2024
  2. 2Efficient Model on Corp Disease and Pest Detection with Deep Learning2024
  3. 3Deep Learning Approaches for Crop Health Monitoring and Early Disease Detection: A Review2025 · 1 citations
  4. 4Application of Machine Learning and Deep Learning in Precision Agriculture for Crop Disease Detection and Pest Management2025
  5. 5Plant Disease Detection Using Deep Learning2025