Fast and Accurate Detection and Classification of Plant Diseases

748 citations recorded by the source corpus.

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

Plant leaf disease classification using EfficientNet deep learning model (2021, methodology): “…et al. performed the segmentation of the diseased areas by clustering the properties obtained with the preprocessing steps using K-Means, and then classified those regions with Artificial Neural Networks (ANN) after performing color and texture based feature extraction (Al-Hiary et al., 2011).”
Detection of unhealthy region of plant leaves and classification of plant leaf diseases using texture features (2013, background): “Further, in some developing countries, farmers may have to go long distances to contact experts, this makes consulting experts too expensive and time consuming (Al-Hiary et al., 2011) and moreover farmers are unaware of non-native diseases.”
Deep Learning for Tomato Diseases: Classification and Symptoms Visualization (2017, methodology): “Therefore, most of the previous reports include the use of small labeled datasets (10 – 800 images) to train and evaluate the accuracy of the proposed studies (Akhtar et al. 2013; Al Hiary et al. 2011; Dandawate and Kokare 2015; Mokhtar et al. 2015).”