Using wavelet transform and hybrid CNN – LSTM models on VOC & ultrasound IoT sensor data for non-visual maize disease detection

Using wavelet transform and hybrid CNN – LSTM models on VOC & ultrasound IoT sensor data for non-visual maize disease detection

Early detection of plant diseases is crucial for safeguarding crop yield, especially in regions vulnerable to food insecurity, such as Sub-Saharan Africa. One of the significant contributors to maize crop yield loss is the Northern Leaf Blight (NLB), which traditionally takes 14–21 days to visually...

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Bibliographic Details
Main Authors: Theofrida Julius Maginga, Emmanuel Masabo, Pierre Bakunzibake, Kwang Soo Kim, Jimmy Nsenga
Format: Article
Language:English
Published: Elsevier 2024-02-01
Series:Heliyon
Subjects:
CNN
LSTM
Wavelet
VOC
Ultrasound
Maize
Online Access:http://www.sciencedirect.com/science/article/pii/S2405844024026781

Internet

http://www.sciencedirect.com/science/article/pii/S2405844024026781

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