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This study aims at classification of different diseases occurring in the Sugarcane plant through the analysis of the plant leaves including red rot and red rust. The work applies the use of classification techniques based upon deep learning methodologies to detect and classify- Red Rot and Red Rust diseases which are common in the plants of sugarcane. Deep learning algorithms are known to be highly efficient in classification tasks. The study addresses usage of five transfer learning models based on deep learning—DenseNet201 alongside Naive Bayes, VGG16 with SVM and ResNet50 with SVM and KNN, and evaluates the performance of the models.

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Deep Learning Disease Classification in Sugarcane Plants Through Leaf Analysis

  • 会议论文

  • 发表日期：

    2025年

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  • Simran Vishrant,
  • Bhawna,
  • Vibha Pratap

摘要

This study aims at classification of different diseases occurring in the Sugarcane plant through the analysis of the plant leaves including red rot and red rust. The work applies the use of classification techniques based upon deep learning methodologies to detect and classify- Red Rot and Red Rust diseases which are common in the plants of sugarcane. Deep learning algorithms are known to be highly efficient in classification tasks. The study addresses usage of five transfer learning models based on deep learning—DenseNet201 alongside Naive Bayes, VGG16 with SVM and ResNet50 with SVM and KNN, and evaluates the performance of the models.