[HTML][HTML] TinyML for Smart Agriculture: Comparative Analysis of TinyML Platforms and Practical Deployment for Maize Leaf Disease Identification
DAN Gookyi, FA Wulnye, EAE Arthur… - Smart Agricultural …, 2024 - Elsevier
Maize, a vital global food crop, is susceptible to various diseases impacting agricultural yield
and quality, necessitating effective monitoring strategies. This study presents a
comprehensive approach utilizing advanced Convolutional Neural Network (CNN)
architecture for efficient maize leaf disease detection and classification. Leveraging datasets
from Kaggle, Harvard Dataverse, and Mendeley, the proposed CNN maize disease
detection (MDD) system integrates optimization techniques, data augmentation, batch size …
and quality, necessitating effective monitoring strategies. This study presents a
comprehensive approach utilizing advanced Convolutional Neural Network (CNN)
architecture for efficient maize leaf disease detection and classification. Leveraging datasets
from Kaggle, Harvard Dataverse, and Mendeley, the proposed CNN maize disease
detection (MDD) system integrates optimization techniques, data augmentation, batch size …
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