Plant diseases and pests detection based on deep learning: a review

By Jun Liu, Xuewei Wang. Plant Methods, 2021

799 citations recorded by the source corpus.

Plant diseases and pests are important factors determining the yield and quality of plants. Plant diseases and pests identification can be carried out by means of digital image processing. In recent years, deep learning has made breakthroughs in the field of digital image processing, far superior to traditional methods. How to use deep learning technology to study plant diseases and pests identification has become a research issue of great concern to researchers. This review provides a definition of plant diseases and pests detection problem, puts forward a comparison with traditional plant diseases and pests detection methods. According to the difference of network structure, this study outlines the research on plant diseases and pests detection based on deep learning in recent years from three aspects of classification network, detection network and segmentation network, and the advantages and disadvantages of each method are summarized. Common datasets are introduced, and the performance of existing studies is compared. On this basis, this study discusses possible challenges in practical applications of plant diseases and pests detection based on deep learning. In addition, possible solutions and research ideas are proposed for the challenges, and several suggestions are given. Finally, this study gives the analysis and prospect of the future trend of plant diseases and pests detection based on deep learning.

Subfields: Plant Science

View Paper: https://www.semanticscholar.org/paper/b415adc22ac3133c82078c987303c422c56b3b5e

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Citations in the corpus

Plant disease detection and classification techniques: a comparative study of the performances (2024, neutral): “The f1-score considers both the model’s precision and recall [34].”
A Survey of Deep Convolutional Neural Networks Applied for Prediction of Plant Leaf Diseases (2021, background): “presented the review of deep learning models employed for plant pest and disease prediction [54].”
An advanced deep learning models-based plant disease detection: A review of recent research (2023, methodology): “These methods involve training a network to learn the underlying features of the images, enabling the identification of subtle symptoms of diseases that traditional image processing methods may not be able to detect (Singh and Misra, 2017; Khan et al., 2021; Liu and Wang, 2021b).”