Multi-class Plant Leaf Image Disease Prediction Using Deep Learning Algorithm

Globally, plant diseases are the main factor in agricultural losses, which has an effect on the worldwide economy. Deep neural network concepts for early disease diagnosis and control are part of the smart agricultural solutions that are developing to address these problems. Utilizing precise or automatic detection methods, early identification of plant diseases can improve food production quality and reduce financial losses. In this paper, we introduced the Enhanced Vision Transform Classification (EVTC) neural network model for effective plant disease identification. In recent years, deep learning has substantially improved the accuracy of object detection and image categorization systems. The trials made use of the well-known PlantVillage dataset, which contains 54,305 images of various plant disease varieties classified into 38 classes.

• Publication year

  2022

• Venue

  2022 International Conference on Knowledge Engineering and Communication Systems (ICKES)

• Publication date

  2022-12-28

• Fields of study

  Not labeled

• Identifiers
  DOI 10.1109/ICKECS56523.2022.10059590
• External record

  Open on Semantic Scholar

• Source metadata

  Semantic Scholar

• No claims are published for this paper.

• No concepts are published for this paper.

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