config_file: ":/yolox_l_dwpose_ucoco.yaml" - model_name: "rtdetr_r50-r20230520" config_file: ":/rtdetr_r50.yaml" - model_name: "yolov5n_obb_drone_vehicle-r20231024" config_file: ":/yolov5n_obb_drone_vehicle.yaml" - model_name: "yolov5s_obb_csl_dotav10-r20231024" config_...
For our experiments, we utilized the NVIDIA Jetson Nano to support YOLOv9-based drone detection. The performance evaluation of YOLOv9 to detect drones is based on metrics like mean average precision (mAP), frames per second (FPS), precision, recall, and F1-score. Experimental data revealed ...
Using YOLOv5, SAHI, and GIS with Drone Mapping to Detect Giant Clams on the Great Barrier ReefDespite the ecological importance of giant clams (Tridacninae), their effective management and conservation is challenging due to their widespread distribution and labour-intensive monitoring methods. In ...
This paper addresses the complexity of forest and mountain fire detection by proposing YOLO-CSQ, a drone-based fire detection method built upon an improved YOLOv8 algorithm. Firstly, we introduce the CBAM attention mechanism, which enhances the model’s multi-scale fire feature extraction ...