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October 17, 2025International Journal of Advanced Research in Science Communication and TechnologyOpen Access

Plant Health AI Analyzer Using Supervised Learning

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Authors

SMSoham ModiV-Vishal Misal -SKShraddha Kulkarni

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Implication

AI-driven tool demonstrates improved disease classification in crops, suggesting benefits for food security and quality.

Key Points

  • This research aims to develop an AI-based analyzer to accurately detect plant diseases and enhance agricultural productivity.
  • Implemented Convolutional Neural Networks for disease classification
  • Utilized the Plant Village dataset for training
  • Employed cross-entropy loss and Adam optimizer in model optimization
  • Created a web interface for real-time diagnostics using Flask
  • Applied data augmentation techniques to improve model generalization.
  • Achieved high accuracy in multi-class disease prediction
  • Demonstrated effective early detection of plant diseases
  • Supported sustainable farming through enhanced precision agriculture techniques.

Cite This Study

Modi et al. (2025) studied this question.

synapsesocial.com/papers/69254f92c0ce034ddc359c79https://doi.org/10.48175/ijarsct-29519
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