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Analysis Study Research Paper | Computer Engineering | India | Volume 12 Issue 8, August 2023
Automated Agricultural Plant Leaf Disease Detection using Butterfly Optimization Algorithm with Deep Learning
D. Raja [8] | Dr. M. Karthikeyan [3]
Abstract: Plant leaf disease automated classification and recognition can play a significant part in reducing these threats. Agricultural Plant Leaf Disease Detection (APLDD) model is Computer Vision (CV) based process developed for automatic classification and recognition of abnormalities or ailments in plant leaves. This approach can play a critical part in precision farming by allowing initial recognition and appropriate interference in preventing the disease's spread and reducing the loss of crops. By the influence of CV and Deep Learning (DL), the APLDD technique can remarkably assist scientists and agriculturalists in employing proactive measures in safeguarding crops, promote sustainable farming routines, and enhance yields. Therefore, this article presents an Automated Agricultural Plant Leaf Disease Detection using Butterfly Optimization Algorithm with Deep Learning (APLDD - BOADL) technique. The presented model integrates VGG16 for feature extraction, Butterfly Optimization Algorithm (BOA) for hyperparameter tuning, and Long Short - Term Memory (LSTM) for disease classification. The VGG16 architecture is exploited for the generation of high - level features from these images. For optimizing the results of the VGG16 model, Butterfly Optimization Algorithm (BOA) is applied for hyperparameter tuning process. Finally, the LSTM classification enables accurate disease identification and differentiation between healthy and diseased leaves. The results demonstrate the superior accuracy and robustness of our approach compared to traditional methods.
Keywords: Agriculture, Plant disease detection, Computer vision, Deep learning, Butterfly optimization algorithm
Edition: Volume 12 Issue 8, August 2023,
Pages: 235 - 243