Authors - Rydhm Beri, Parul Sachdeva Abstract - Plant diseases present a serious threat to all forms of life. Early detection is vital which allows farmers to take prompt action, improving both their response and productivity. Our research centers on five common rice leaf diseases—bacterial leaf blight, leaf blast, brown spot, leaf scald, and narrow brown spot—along with a category for healthy leaves. Additionally, we examine two types of betel leaves: healthy and unhealthy. This study propose an innovative deep ensemble model that combines the EfficientNetV2L, InceptionResNetV2, and Xception architectures. This model addresses issues of underfitting and performance by utilizing advanced techniques including data augmentation, Global Average Pooling, preprocessing, Dropout, L2 regularization, PReLU activation, Batch Normalization, and multiple Dense layers. This robust approach surpasses existing models by managing both underfitting and overfitting, while delivering superior performance.
Open Zoom
