Automated Rice Leaf Disease Detection Using Deep Feature Extraction and Machine Learning Classification

This research introduces an InceptionV3 and EfficientNetB0 based deep feature extraction hybrid with PCA dimensionality reduction and multi-classifiers based machine learning for leaf disease detection of hybrid rice. The proposed InceptionV3 – PCA – SVM model reached an accuracy of 99.66% and a mobile application was also developed offline for real-time disease detection without the need for internet connectivity.