Flood Survivor Detection through Image Fusion and Yolo Model

Natural disasters like flood happen when water overtakes normally dry places. During rescue missions aimed at saving lives, rescue teams responding to floods encounter numerous obstacles. Locating and discovering survivors is a vital component of rescue operations. For quick flood survivor recognition, the suggested approach combines image fusion with the YOLO (You Only Look Once) model, offering a novel method. This model utilizes image fusion by merging data from various sources, including RGB and Near Infrared Red (NIR) images captured by Unmanned Aerial Vehicles (UAVs). In order to efficiently identify flood survivors and aid rescue crews in their effort to preserve lives, the resulting fused image is processed using the YOLO model.