The YOLOv8 Edge: Harnessing Custom Datasets for Superior Real-time Detection
The paper details a YOLOv8 model trained on custom datasets, achieving a mAP50 of 0.864 and a mAP50-95 of 0.758 for detecting objects in real-time streams, demonstrating advancements in accuracy and speed.