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Ultralytics Live Session 15: Enhancing Object Detection with Roboflow 100 and Ultralytics YOLO



Join us for Ultralytics Live Session 15, featuring Ultralytics Founder and CEO Glenn Jocher, and Joseph Nelson, Co-Founder at Roboflow. In this engaging session, we delve into the Roboflow 100 (RF100) Datasets and their integration with Ultralytics YOLO models. The RF100, developed by Roboflow and sponsored by Intel, is an object detection benchmark comprising 100 diverse datasets sampled from over 90,000 public datasets. Designed to test the adaptability of models across various domains, including healthcare, aerial imagery, and video games, RF100 is revolutionizing how we measure model performance.

🔍 Key highlights of the video:
– Introduction to the RF100 Dataset
– Demonstration of dataset applications
– Discussion on model generalizability
– Insights into the future of computer vision
– Live Q&A session

Discover how over 500,000 developers and ML engineers utilize Roboflow to build and deploy computer vision models. Joseph Nelson shares his expertise in computer vision and his mission to democratize AI, making it accessible for every industry.

Explore how Ultralytics YOLO models, including YOLOv5 and YOLOv8, are pushing the boundaries of what’s possible in computer vision. Learn how these models perform across the RF100 datasets and get an exclusive first look at a new benchmarking tool integrated into the Ultralytics Python package.

📚 Dive deeper with these resources:
– RF100 Dataset Documentation: https://docs.ultralytics.com/datasets/detect/roboflow-100/
– Ultralytics HUB: https://www.ultralytics.com/hub
– Explore Ultralytics YOLOv8: https://www.ultralytics.com/yolo
– AI Insights Blog: https://www.ultralytics.com/blog/roboflow-on-building-with-open-source-and-ultralytics-yolov8

Join us in advancing the field of computer vision! Don’t forget to like, subscribe, and hit the notification bell for more updates.

#YOLO #Ultralytics #ComputerVision #AI #Roboflow #MachineLearning #DeepLearning #YOLOv8 #AIInnovation #ComputerVisionModels

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