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Automatic Fuzzy Logic-Based Maize Common Rust Disease Severity Predictions with Thresholding and Deep Learning.

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第一作者： Malusi,Sibiya

第一单位： Department of Electrical and Mining Engineering, University of South Africa, 28 Pioneer Ave, Florida Park, Johannesburg, Roodepoort 1709, South Africa.

作者： Malusi,Sibiya ^[1] ; Mbuyu,Sumbwanyambe ^[1]

作者单位： Department of Electrical and Mining Engineering, University of South Africa, 28 Pioneer Ave, Florida Park, Johannesburg, Roodepoort 1709, South Africa. ^[1]

关键词 Image Analyzer Otsu threshold method VGG-16 common rust convolutional neural networks fuzzy decision rules image histograms

DOI 10.3390/pathogens10020131

PMID 33525312

发布时间 2021-03-16

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Pathogens (Basel, Switzerland)

2021年10卷2期

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Automatic Fuzzy Logic-Based Maize Common Rust Disease Severity Predictions with Thresholding and Deep Learning.

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Automatic Fuzzy Logic-Based Maize Common Rust Disease Severity Predictions with Thresholding and Deep Learning.

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