Deep Learning Red Palm Weevil Detection | Thermal Image Classifier (ResNet50 Backbone) скачать в хорошем качестве

Deep Learning Red Palm Weevil Detection | Thermal Image Classifier (ResNet50 Backbone)

In this project, I built a deep learning - based thermal image classifier to detect Red Palm Weevil infestations, one of the most destructive pests affecting palm trees worldwide. The model is based on a ResNet50 backbone, leveraging transfer learning to extract high-level spatial features from thermal imagery. By analyzing temperature patterns that are invisible to the human eye, the system can identify early signs of infestation before visible damage appears. 🔍 Project Highlights Thermal image - based classification Deep learning model using ResNet50 Focus on early detection of Red Palm Weevil activity Designed and trained as part of an academic project Practical application for agriculture and environmental monitoring 🧠 Why Thermal + Deep Learning? Red Palm Weevils generate heat due to internal activity inside the tree. Thermal imaging combined with deep neural networks allows accurate, non-invasive detection — helping prevent large-scale damage and tree loss. This project demonstrates how computer vision and deep learning can be applied to real-world environmental and agricultural challenges. If you enjoyed this project or found it useful, feel free to like, comment, or subscribe 🚀 Questions and feedback are always welcome!