Transfer Learning Method for Tomatoes Diseases Detection

Implemented a robust transfer learning method, utilizing the advanced InceptionV3 neural network architecture, for precise identification of tomato diseases. Employed meticulously curated data to enhance model performance. The project encompassed thorough data preprocessing, model training, and seamless deployment with Fast API to the cloud (AWS).

This resulted in a dependable solution for the early detection and management of diseases in tomato crops. Notably, the model was seamlessly integrated into a user-friendly mobile application tailored for farmers. Achieving an impressive accuracy of 97%, the neural network project garnered positive feedback from users, with farmers expressing high satisfaction in its accurate and impactful assistance.