Getting Started with YOLO for Real-Time Object Detection

YOLO (You Only Look Once) is one of the most popular real-time object detection frameworks. In this article, I share what I learned building sign language recognition systems with YOLO and YOLO-NAS.

What is YOLO?

YOLO treats object detection as a regression problem — it predicts bounding boxes and class probabilities simultaneously in a single forward pass. This makes it extremely fast for real-time applications.

Why YOLO-NAS for Sign Language?

YOLO-NAS (Neural Architecture Search) offers superior accuracy compared to previous YOLO versions for small object detection — critical for detecting hand gestures and finger positions accurately.

Key Takeaways

• ▸Use pretrained weights and fine-tune on your domain-specific data
• ▸Data augmentation is critical — especially for hand gesture variety
• ▸YOLO-NAS outperformed YOLOv8 on our ISL dataset by ~15%
• ▸Keep confidence thresholds around 0.4 for sign language to reduce false negatives