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Dive into this 16-minute tutorial where Roboflow's machine learning team explores RF-DETR, a state-of-the-art object detection model that outperforms YOLO. Learn about RF-DETR's architecture, benchmark results, and how to implement it in your computer vision projects. Follow along as the team demonstrates the training process, builds a workflow to compare RF-DETR with YOLOv11, and explains deployment strategies, pre-training techniques, and key benefits. The video is structured with clear sections covering introduction to the team, RF-DETR fundamentals and performance metrics, step-by-step training instructions, comparative testing workflows, and deployment considerations to help you leverage this advanced object detection technology in your applications.
Syllabus
00:00 Intro & Meeting the team
00:53 What is RF-DETR & Benchmarking Results
️♀️ 03:23 How to Train a Model with RF-DETR
⚖️ 06:19 Building a Workflow to Test & Compare with YOLOv11
10:42 Deployment, Behind-the-Scenes Pre-Training, and Benefits
Taught by
Roboflow