2021
DOI: 10.11591/ijece.v11i2.pp1719-1727
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Detection of citrus leaf diseases using a deep learning technique

Abstract: The food security major threats are the diseases affected in plants such as citrus so that the identification in an earlier time is very important. Convenient malady recognition can assist the client with responding immediately and sketch for some guarded activities. This recognition can be completed without a human by utilizing plant leaf pictures. There are many methods employed for the classification and detection in machine learning (ML) models, but the combination of increasing advances in computer vision… Show more

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Cited by 33 publications
(26 citation statements)
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“…Due to various parameter configurations of layers in a convolutional neural network like filters, filter size, batch size, number of epochs, and various measures like accuracy, recall, and F1 measure, the proposed approach outperformed the baseline work. Luaibi et al [7] claim an accuracy of 93.75 percent on the given dataset, but we found an accuracy of 92.20 percent on the same dataset when we experimented.…”
Section: • Cnn (Proposed) Vs Baseline#2mentioning
confidence: 45%
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“…Due to various parameter configurations of layers in a convolutional neural network like filters, filter size, batch size, number of epochs, and various measures like accuracy, recall, and F1 measure, the proposed approach outperformed the baseline work. Luaibi et al [7] claim an accuracy of 93.75 percent on the given dataset, but we found an accuracy of 92.20 percent on the same dataset when we experimented.…”
Section: • Cnn (Proposed) Vs Baseline#2mentioning
confidence: 45%
“…The results also show that the maximum accuracy was achieved through the use of CNN with various convolution layers. The aforesaid results demonstrate that, in terms of Citrus disease recognition, the suggested CNN model reached the best performance level (94.55% accuracy) than the other deep and machine-learning work [7,23,24,32]. The proposed model's best accuracy over the benchmark works is due to the use of CNN, which is intended for image processing.…”
Section: Discussion Of the Results Obtainedmentioning
confidence: 80%
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