Feature Extraction with Triplet Loss to Classify Disease on Leaf Data

This paper addresses the plant disease detection and classification using Deep Learning approach. In particular, we propose a novel model using the Triplet Loss together with the fine-tuned pre-trained MobileNet model to extract good features, classify, and detect diseases of plants from the open-source PlantVillage dataset. Using our proposed model, the achievable results are 99.92%, which outperforms the existing models using the same dataset. Furthermore, our proposed model can support the large-scale agricultural sector, which plays an important role in ensuring food security during the current COVID-19 crisis.