Detection of Humans in Search and Rescue Operations Using Ensemble Learning and YOLOv9

Ananya Basireddy, K. Gangadhara Rao, Vaishnavi Vaitla, Soumil Reddy Pedda

2025

Abstract

This project focuses on developing a robust and efficient human detection system for Search and Rescue (SAR) operations using advanced deep learning techniques. The proposed system integrates EfficientDet, which leverages EfficientNet as the backbone for feature extraction, and YOLOv9, known for real-time object detection, to maximize both accuracy and speed in complex environments. To enhance the system’s capability in detecting humans under various conditions, the model incorporates thermal imaging, RGB images, and ensemble learning techniques like Non-Maximum Suppression (NMS) and confidence-weighted voting. Additionally, the model is trained using the Heridal and Aerial Rescue Object Detection datasets, which include images from real-world SAR environments. Incorporating BiFPN (Bidirectional Feature Pyramid Network) and FC-FPN (Fully Connected Feature Pyramid Network) architectures into the system allows for multi-scale feature fusion, improving detection of humans at different scales and orientations, even in low-visibility scenarios. Furthermore, the project integrates deblurring and dehazing techniques to enhance image quality from aerial footage, making it easier to detect partially occluded or camouflaged humans. The system is designed to operate on UAVs, with the capability to send automated alerts via email and SMS, including geolocation data of detected individuals, ensuring quick response in disaster recovery missions. The results demonstrate the system’s high accuracy and efficiency in detecting humans in various challenging environments, making it a valuable tool for autonomous SAR missions.

Paper Citation

in Harvard Style

Basireddy A., Rao K., Vaitla V. and Pedda S. (2025). Detection of Humans in Search and Rescue Operations Using Ensemble Learning and YOLOv9. In Proceedings of the 3rd International Conference on Futuristic Technology - Volume 2: INCOFT; ISBN 978-989-758-763-4, SciTePress, pages 923-928. DOI: 10.5220/0013607400004664

in Bibtex Style

@conference{incoft25,
author={Ananya Basireddy and K. Gangadhara Rao and Vaishnavi Vaitla and Soumil Reddy Pedda},
title={Detection of Humans in Search and Rescue Operations Using Ensemble Learning and YOLOv9},
booktitle={Proceedings of the 3rd International Conference on Futuristic Technology - Volume 2: INCOFT},
year={2025},
pages={923-928},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0013607400004664},
isbn={978-989-758-763-4},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 3rd International Conference on Futuristic Technology - Volume 2: INCOFT
TI - Detection of Humans in Search and Rescue Operations Using Ensemble Learning and YOLOv9
SN - 978-989-758-763-4
AU - Basireddy A.
AU - Rao K.
AU - Vaitla V.
AU - Pedda S.
PY - 2025
SP - 923
EP - 928
DO - 10.5220/0013607400004664
PB - SciTePress