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Dual-Model Drone Detection with YOLOv5 by Selena Jasmine is a document available to read on EtoBox.
What is Dual-Model Drone Detection with YOLOv5 about?
This paper presents a dual-model drone detection system using YOLOv5 trained on both RGB and thermal imagery, addressing security challenges posed by small drones. The models achieved high detection accuracy with precision around 100% and recall approximately 98%, and a Streamlit web application was developed for real-time detection. The findings suggest that the dual-model approach enhances drone monitoring capabilities in various conditions, making it suitable for applications in security and surveillance
- Author
- Selena Jasmine
- Language
- EN