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EfficientNet based Convolutional Neural Network for Visual Plant Disease Detection

Crops grown in tropical, subtropical, and temperate climates are subject to a variety of diseases and pests. Plant illnesses are complicated by interactions between the virus, the host plant, and the insect. In this paper, we present a robust transfer-learning-based detector for real-time plant disease detection with PlantDoc datasets and plant village dataset. EfficientNetV2 architecture is more efficient, high speed and accurate in compared with EfficientNetV1. The EfficientNetV2 with the pretrained weights, Image net and plant village obtain the highest score in accuracy with 74%,F1-score=0.74 if compared to other benchmarked models.