Deep Learning-Based Cucumber Leaf Disease Detection uses AI to identify diseases from leaf images, helping farmers reduce crop loss and improve productivity through smart technology.
My project, Deep Learning-Based Cucumber Leaf Disease Detection, uses the EfficientNet architecture to accurately identify diseases from cucumber leaf images. The model was trained on a custom dataset and achieved 95% accuracy in classification. This system enables early disease detection and supports farmers in reducing crop loss through an intelligent and practical application.
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I’m excited to share progress on my Deep Learning–based cucumber leaf disease detection project. The model is built using EfficientNet and achieved 95% accuracy on a custom dataset. I improved performance through data augmentation, preprocessing, and transfer learning techniques. I’m currently working on a mobile app for real-time disease prediction using camera input. The goal is to support farmers with fast, accurate, and accessible AI-based crop disease diagnosis.
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