articleIEEE AccessJan 1, 2022GOLD OA

End-to-End Deep Learning Model for Corn Leaf Disease Classification

Helwan University · Scientific Research Group in Egypt · +1 more institution

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Abstract

Plant diseases compose a great threat to global food security. However, the rapid identification of plant diseases remains challenging and time-consuming. It requires experts to accurately identify if the plant is healthy or not and identify the type of infection. Deep learning techniques have recently been used to identify and diagnose diseased plants from digital images to help automate plant disease diagnosis and help non-experts identify diseased plants. While many deep learning applications have been used to identify diseased plants and aims to increase the detection rate, the limitation of the large parameter size in the models persist. In this paper, an end-to-end deep learning model is developed to…

Citation impact

251
total citations
FWCI
46.82
Percentile
100%
References
24
Citations per year

Authors

4

Topics & keywords

Keywords
  • Deep learning
  • Artificial intelligence
  • Convolutional neural network
  • Computer science
  • Plant disease
  • Machine learning
  • Concatenation (mathematics)
  • Pattern recognition (psychology)
UN Sustainable Development Goals
  • Zero hunger
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