Thread by @nevrekaraishwa2

📣 Object detection enthusiasts, I have some exciting news for you! 📣

🏎️ @deci_ai brings you YOLO-based architecture, YOLO-NAS for object detection which has just been open-sourced!

A Game-Changer for Enthusiasts!

A thread🧵👇

1. What's the NAS all about?

Researchers at Deci used Neural Architecture Search (NAS) to automate the discovery of an optimal object detection architecture.

🤯 They used deep learning to find a new deep learning architecture!

2. Key points about YOLO-NAS:

🛩️ Enhanced detection of small objects, improved localization accuracy, and performance-per-compute ratio.
📱 Ideal for real-time edge-device applications.
🧱 Incorporates quantization-aware RepVGG blocks and applies them for optimal performance.

3. 💡 Leverages attention mechanisms, quantization-aware blocks, and reparametrization at inference time, setting a new gold standard for object detection across industries.

4. 🏋️ Trained in a multi-phase process involving pre-training on Object365, COCO Pseudo-Labeled data, Knowledge Distillation (KD), and Distribution Focal Loss (DFL).

5. 📊 Outperforms existing YOLO models on the diverse RoboFlow100 (RF100) dataset, following a robust training protocol, providing significant advantages in various use cases. 🏆

Make sure to star the SuperGradients GitHub repo, play around with the starter notebook and let's revolutionize the field of computer vision together. 💫
GitHub repo: bit.ly/yolo-nas-launch

Try out this starter notebook to get introduced to the SuperGradients library + YOLONAS model

Starter NB Link: bit.ly/yolo-nas-start…

Thank you so much for reading this, for more such posts follow @nevrekaraishwa2
#yolonas #computervision #yolov8