This project presents FarmPest Guide, a deep learning–based application designed to classify dangerous farm insects that pose threats to agricultural productivity. The system aims to assist farmers, agricultural practitioners, and the general public in identifying dangerous farm insects through image-based classification. In addition to classification results, the application provides informative outputs such as pest descriptions, potential impacts, danger levels, and recommended handling or mitigation methods. By integrating artificial intelligence into agriculture, this project contributes to early pest detection and improved crop protection strategies.
The FarmPest Guide application has been successfully deployed and can be accessed through the following link:
🔗 Deployed Application (Hugging Face Spaces): https://huggingface.co/spaces/DG226/DeepLearning
Users can upload insect images directly through the web interface and receive real-time classification results along with relevant pest information.
Additional materials related to this project are provided below:
A demonstration video showcasing the application workflow, features, and classification results:
A complete presentation explaining the background, methodology, model architecture, experimental results, and conclusions of the project:
This project was developed as part of a final deep learning course assignment and demonstrates the practical application of computer vision techniques in the agricultural domain.